-
Maximus TCS (Technology and Consulting Services) Internal Job Profile Code: TCS219, T3, Band 6
Job - Specific Essentials Responsibilities:
- Serve as a senior technical lead and escalation point across mission-critical enterprise environments
- Provide technical direction, mentoring, workload coordination, and supervision for Windows administrators and supporting technical staff
- Administer, configure, patch, secure, and optimize Windows Server infrastructure while monitoring system health, performance, and availability
- Lead troubleshooting, root cause analysis, incident response, break/fix support, and service restoration
- Develop and maintain patching, upgrade, backup, restoration, and disaster recovery plans to support high availability and operational readiness
- Coordinate with cybersecurity, network, database, application, storage, and operations teams to ensure system reliability, security, and compliance
- Create and maintain system documentation, standard operating procedures (SOPs), runbooks, configuration guides, and knowledge transfer materials
- Install, configure, and troubleshoot applications, software tools, operating systems, and enterprise Windows services
- Support the management, maintenance, and operational readiness of backup and restore platform hardware and software
- Manage desktop tools and support virtual desktop infrastructure (VDI) and remote desktop environments
- Support Microsoft clustering technologies, including Exchange and Microsoft SQL Server (MSSQL) clustered environments
- Perform other duties as assigned
Job- Specific Minimum Requirements:
-Active Secret Clearance is required.
- Due to contract requirements, only US Citizens can be considered.
- 7 or more years of experience or equivalent in the following:
* Dell Enterprise Servers with iDRAC and Dell Lights Out Management
* MS domain infrastructure: Active Directory, DNS, DHCP, DFS, Network Policy Server, distributed patch, security, and Exchange
* Omnissa (VMware) VDI infrastructure and services; backend and frontend
* MS Windows 11
* HBSS Clients on Windows Operating Systems
* Familiarity with third-party backup and restore methodologies on Windows Operating Systems
- Candidates must reside within a commutable distance for daily onsite work and on-call requirements.
- This contract supports systems that require 24x7x365 uptime.
Candidates must be willing and able to meet recall requirements, including participation in a rotational on-call schedule.
Minimum Requirements
TCS219, T3, Band 6
EEO Statement
Maximus is an equal opportunity employer.
We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expect...
....Read more...
Type: Permanent Location: Colorado Springs, US-CO
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:28
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I: Essential Job Functions:
• Define functional and non-functional requirements that systems must perform, define the user's perspective on system usage ("user stories"), use cases, and define the conditions which a system must meet to be considered complete with input and guidance from product owner.
• Conduct business process analysis and workflow mapping to translate user needs into technical specifications and system design artifacts.
• Document the functional design of the system integrating feedback from product owners, developers, and architects.
• Test end to end functionality for Maximus Provider Connexion ("MPC") including Customer Relationship Management ("CRM") and Genesys integration.
• Ensure and review that the business/technical requirements are understood and participate in scrum team ceremonies to review the requirements with the development team.
• Draft and review user stories with product owners, developers and testers.
• Create and execute test cases against defined and approved user stories.
• Review and create user manuals based on functional designs.
• Create and maintain business solution blueprints with product owner oversight.
• Prepare detailed acceptance criteria alongside user stories and use cases.
• Participate in Agile ceremonies beyond requirement reviews (e.g., sprint planning, retrospectives).
• Log and track defects and collaborate on resolution for production readiness.
• Create workflow diagrams and process documentation under product-owner oversight.
• Develop quick-reference guides and training materials to supplement user manuals.
• Collaborate with User Interface teams to review wireframes, create mockups using Balsamiq and Enforce standard UX guidelines for consistent design.
• Collaborate with QA, UX, and DevOps teams to verify deployment readiness and maintain compliance with healthcare data-management standards (HIPAA)
• Work with the performance team to support user stories and contribute to drafting technical spikes for developers.
II: Education and Experience Required:
• Bachelor's degree in Information Science, Computer Science, Information Technology, or a closely related field plus 5 years experience in State Medicaid healthcare systems, and experience supporting requirements gathering, business and technical design, and testing of healthcare systems in an Agile environment, of which 2 years included experience as a Subject Matter Expert in Call Center Integration, Customer Relationship Management and Provider Management Systems.
III.
Special Skills Required:
Agile & Project Management
• Agile/Scrum, Kanban
• JIRA, Confluence
Business Analysis & Healthcare
• Requirements, user stories, acceptance criteria
• Process modeling, BPMN diagrams, documentation
• Stakeholder communication, HIPAA compliance
Testing & Quality Assurance
• Test case design, execution
• Defect tracking (JIRA)
• API validation (Postman)
D...
....Read more...
Type: Permanent Location: Mclean, US-VA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:27
-
Maximus TCS (Technology and Consulting Services) Internal Job Profile Code: TCS219, T3, Band 6
Job - Specific Essentials Responsibilities:
- Serve as a senior technical lead and escalation point across mission-critical enterprise environments
- Provide technical direction, mentoring, workload coordination, and supervision for Windows administrators and supporting technical staff
- Administer, configure, patch, secure, and optimize Windows Server infrastructure while monitoring system health, performance, and availability
- Lead troubleshooting, root cause analysis, incident response, break/fix support, and service restoration
- Develop and maintain patching, upgrade, backup, restoration, and disaster recovery plans to support high availability and operational readiness
- Coordinate with cybersecurity, network, database, application, storage, and operations teams to ensure system reliability, security, and compliance
- Create and maintain system documentation, standard operating procedures (SOPs), runbooks, configuration guides, and knowledge transfer materials
- Install, configure, and troubleshoot applications, software tools, operating systems, and enterprise Windows services
- Support the management, maintenance, and operational readiness of backup and restore platform hardware and software
- Manage desktop tools and support virtual desktop infrastructure (VDI) and remote desktop environments
- Support Microsoft clustering technologies, including Exchange and Microsoft SQL Server (MSSQL) clustered environments
- Perform other duties as assigned
Job- Specific Minimum Requirements:
Active Secret Clearance is required.
- Due to contract requirements, only US Citizens can be considered.
- 7 or more years of experience or equivalent in the following:
* Dell Enterprise Servers with iDRAC and Dell Lights Out Management
* MS domain infrastructure: Active Directory, DNS, DHCP, DFS, Network Policy Server, distributed patch, security, and Exchange
* Omnissa (VMware) VDI infrastructure and services; backend and frontend
* MS Windows 11
* HBSS Clients on Windows Operating Systems
* Familiarity with third-party backup and restore methodologies on Windows Operating Systems
- Candidates must reside within a commutable distance for daily onsite work and on-call requirements.
- This contract supports systems that require 24x7x365 uptime.
Candidates must be willing and able to meet recall requirements, including participation in a rotational on-call schedule.
Minimum Requirements
TCS219, T3, Band 6
EEO Statement
Maximus is an equal opportunity employer.
We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expecte...
....Read more...
Type: Permanent Location: Colorado Springs, US-CO
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:27
-
Maximus TCS (Technology and Consulting Services) Internal Job Profile Code: TCS146, T2, Band 5
Job-Specific Essential Duties and Responsibilities:
- Provide Tier 2 IT support services for a mission-critical platform.
- Supervise Tier 1 Support Specialists, oversee their duties and functions, and serve as a direct line of escalation.
- Assist in developing and maintaining formal standard operating procedures and work instructions to promote consistency and improve operational productivity.
- Create, submit, and follow up on access requests for newly assigned OSC operators.
- Assist in implementing methodologies to improve first-call resolution rates.
- Provide guidance and assistance to ensure the OSC team meets all established Service Level Agreements (SLAs).
- Provide guidance and spot training related to Knowledge Base Articles (KBAs).
- Monitor issue response times and support the operations team in strengthening problem-solving skills.
- Provide effective leadership and communication to manage daily OSC operator activities and coordinate with contract and government stakeholders when support issues arise.
- Ensure OSC operators respond to customer inquiries by phone or IT-based communication tools and can troubleshoot and resolve issues as directed.
- Manage and schedule OSC staff for optimal performance, including resource planning for mission-critical support while accounting for holidays and paid time off.
- Assist in preparing the support team for new product and service releases.
- Maintain current knowledge of industry trends and assess their potential impact on support operations.
- Assist with interviews for new OSC operators and provide feedback to support OSC operator promotions.
- Motivate the team to adhere to IT best practices and deliver outstanding customer service and satisfaction.
- Assist in creating and maintaining a training program to increase business, customer service, and technical knowledge.
- Participate in the organization's change management process.
- Maintain detailed records of incidents, including reporting, classification, and resolution steps for daily and weekly metric reporting.
- Gather and present PMR metric reporting to OSC management, contract leadership, and government stakeholders.
- Use monitoring tools to proactively identify and address potential issues and generate reports on incident trends.
- Provide backup support to the OSC Lead to ensure continuity of daily operations.
- Other duties as assigned.
Minimum Requirements:
- Active Secret clearance is required.
- 7+ years of experience in helpdesk, service desk, call center, or equivalent customer service support.
- Candidates must reside within a commutable distance to support daily onsite work and on-call requirements.
- This role supports a 24x7x365 Operations Center, requiring participation in a rotational on-call schedule and the ability to work up to 12-hour shifts, including weekends and holidays, throughout t...
....Read more...
Type: Permanent Location: Annapolis Junction, US-MD
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:26
-
Essential Duties and Responsibilities:
- Responsible for responding to telephone calls, emails, and personnel requests for technical support.
- Identify, research, and resolve technical problems.
- Document, track, and monitor problems to ensure timely resolution.
- Correct application issues, solve network and security problems, and identify common PC software and hardware problems.
- Assign username, password, and access right permissions for multiple proprietary applications, as well as client software.
Job-Specific Essential Duties and Responsibilities:
- Provide a first point of contact for customers seeking technical assistance with a ticket, phone call, email, or in person
- Assist customers, troubleshoot problems, and coordinate technical support.
- Account creations, account lockouts, password changes
- Record events and problems and their resolution in logs
- Follow-up and update customer status and information
- Log and route service requests and incidents in an incident management system.
- Maintain service level agreements related to Desk Side support Service/Incident requests
- Direct unresolved issues to the next level of support team member
- Establish phone bridge with next level of support and customer leads per SOP's
- Receive and input critical time data in various formats and ingest it into the vetting system.
Data may be received in various formats and must be converted to a customer defined format such as XML for ingest into the system
Job-Specific Minimum Requirements:
- Active Secret clearance is required.
- Due to contract requirements, only US Citizens can be considered.
Candidates with dual citizenship cannot be considered.
- 1-3+ years of experience in Helpdesk/ServiceDesk/Call Center OR equivalent experience in customer service.
- 1-3+ years of experience utilizing any Incident Management Ticketing System such as: § ServiceNow § Other, comparable systems
- This role supports a 24x7x365 Operations Center, requiring participation in a rotational on-call schedule and the ability to work up to 12-hour shifts, including weekends and holidays, throughout the year
#techjobs #clearance #veteransPage
Minimum Requirements
- High school diploma or GED required and 0-2 years of relevant professional experience required, or equivalent combination of education and experience.
EEO Statement
Maximus is an equal opportunity employer.
We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment.
Annual salary is just one component of Maximus's total compens...
....Read more...
Type: Permanent Location: Colorado Springs, US-CO
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:25
-
Essential Duties and Responsibilities:
- Responsible for responding to telephone calls, emails, and personnel requests for technical support.
- Identify, research, and resolve technical problems.
- Document, track, and monitor problems to ensure timely resolution.
- Correct application issues, solve network and security problems, and identify common PC software and hardware problems.
- Assign username, password, and access right permissions for multiple proprietary applications, as well as client software.
Job-Specific Essential Duties and Responsibilities:
- Provide a first point of contact for customers seeking technical assistance with a ticket, phone call, email, or in person
- Assist customers, troubleshoot problems, and coordinate technical support.
- Account creations, account lockouts, password changes
- Record events and problems and their resolution in logs
- Follow-up and update customer status and information
- Log and route service requests and incidents in an incident management system.
- Maintain service level agreements related to Desk Side support Service/Incident requests
- Direct unresolved issues to the next level of support team member
- Establish phone bridge with next level of support and customer leads per SOP's
- Receive and input critical time data in various formats and ingest it into the vetting system.
Data may be received in various formats and must be converted to a customer defined format such as XML for ingest into the system
Job-Specific Minimum Requirements:
- Active Secret clearance is required.
- Due to contract requirements, only US Citizens can be considered.
- 1-3+ years of experience in Helpdesk/ServiceDesk/Call Center OR equivalent experience in customer service.
- 1-3+ years of experience utilizing any Incident Management Ticketing System such as: § ServiceNow § Other, comparable systems
- This role supports a 24x7x365 Operations Center, requiring participation in a rotational on-call schedule and the ability to work up to 12-hour shifts, including weekends and holidays, throughout the year
#techjobs #clearance #veteransPage
Minimum Requirements
- High school diploma or GED required and 0-2 years of relevant professional experience required, or equivalent combination of education and experience.
EEO Statement
Maximus is an equal opportunity employer.
We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment.
Annual salary is just one component of Maximus's total compensation package.
Other rewards may include short- and lon...
....Read more...
Type: Permanent Location: Colorado Springs, US-CO
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:24
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Rock Springs, US-WY
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:22
-
Essential Duties and Responsibilities:
- Establish and communicate monthly QA monitoring targets.
- Manage QA team performance to ensure completion and achievement of established targets.
- Provide required daily and monthly reports to leadership
- Perform trend analysis based on QA evaluation results to improve call center performance and efficiency.
- Utilize trend analysis data to identify and escalate issues, design refresher topics, and improve new hire training.
- Under direction of leadership, research, develop, and implement new features, technologies, new programs and methods to improve QA processes.
- Possess knowledge and skills to perform all direct QA /Training functions if required.
- Perform ad hoc research, reports, analysis, and other duties as assigned by Manager.
- Ensure that all new-hire training classes and refresher classes are properly planned, created, and delivered by the training team.
- Ensure individualized coaching is performed throughout new hire training.
- Ensure a smooth transition of agents to the call center after training.
- Review training surveys and integrate feedback to improve the training program.
- Meet with managers to review training curriculum, technologies, and delivery to improve training quality, trainee readiness, and staff retention.
- Oversee training programs for outreach team, supervisors, leads, and other levels of levels of project staff.
- Ensure all training material updates and improvements are made in a timely manner.
- Develop and improve knowledge testing methods and technologies.
- Perform ad hoc research, reports, analysis, and other duties as assigned by Manager.
Minimum Requirements
- Bachelor's degree in relevant field of study and 3+ years of relevant professional experience required, or equivalent combination of education and experience.
Preferred Experience:
- Prior experience working in a start-up
- Prior experience working with underserved or diverse communities
- Prior experience in QA or training
- Prior experience in creating and implementing recorded training processes
#LI-Onsite #HotJobs0609LI #HotJobs0609FB #HotJobs0609X #HotJobs0609TH #TrendingJobs #c0rejobs #CoreOps
EEO Statement
Maximus is an equal opportunity employer.
We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment.
Annual salary is just one component of Maximus's total compensation package.
Other rewards may include short- and long-term incentives as well as program-specific awards.
Additionally, Maximus pr...
....Read more...
Type: Permanent Location: San Diego, US-CA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:22
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Eau Claire, US-WI
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:21
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Spokane, US-WA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:20
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Cheyenne, US-WY
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:20
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Seattle, US-WA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:19
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Charleston, US-WV
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:18
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Roanoke, US-VA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:18
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Morgantown, US-WV
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:17
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Milwaukee, US-WI
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:17
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Burlington, US-VT
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:16
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Richmond, US-VA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:15
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Tysons, US-VA
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:15
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Bennington, US-VT
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:14
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Salt Lake City, US-UT
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:13
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: St. George, US-UT
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:13
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Lubbock, US-TX
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:12
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: Houston, US-TX
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:11
-
1.
Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
2.
Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
3.
Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
4.
Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
5.
Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
6.
Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
7.
Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.
Key Internal Stakeholders & Relationships
* BI and Analytics Team
* Data Engineering Team
* Data Architect
* Data Governance and Data Quality Teams
* Business Product Owners and Operational SMEs
* Technology Operations and Platform Teams
Key External Stakeholders & Relationships
* External data suppliers
* Partner organisations
Essential & Desirable
Essential
• Degree or equivalent experience in data, analytics, computer science or a related field.
• 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
• Advanced SQL skills, with experience building reusable, tested and well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
• Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
• Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
• Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
• Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.
Desirable
• Experience build...
....Read more...
Type: Permanent Location: San Antonio, US-TX
Salary / Rate: Not Specified
Posted: 2026-10-14 14:59:11
