Analytics Engineer

Purple Wave is seeking a skilled and curious Analytics Engineer to join our growing data organization.

Reporting to the Business Intelligence Manager, this role sits at the intersection of data engineering and analytics, ensuring that raw data is transformed into clean, tested, well-documented datasets that the entire company can trust and use.

This is a remote-eligible individual contributor role responsible for building and maintaining the modeling layer that powers reporting, self-service analytics, and data-driven decision-making across the business.

The Analytics Engineer owns the transformation layer between raw ingested data and the curated, business-ready datasets consumed by analysts, stakeholders, and downstream applications.

Applying software engineering best practices -- version control, testing, documentation, and CI/CD -- to the analytics workflow, this role ensures that data models are reliable, performant, and easy to understand.

The Analytics Engineer partners closely with data engineers, analysts, data scientists, and business stakeholders to translate business logic into modular, maintainable data models and to establish a single source of truth for key metrics and dimensions.

Responsibilities: Data Modeling & Transformation Design, build, and maintain dimensional and analytical data models using dbt (data build tool).

Transform raw and staged data into clean, well-structured datasets optimized for analysis and reporting.

Define and codify core business logic, metrics, and definitions in a central, version-controlled modeling layer.

Develop and enforce modeling conventions (naming, structure, materialization strategies) to ensure consistency across the project.

Data Quality & Testing Write and maintain robust data tests (schema, freshness, custom) to catch issues before they reach consumers.

Monitor data pipeline health and model freshness, triaging and resolving failures promptly.

Collaborate with data engineers to improve source data reliability and establish data contracts where appropriate.

Proactively identify data quality gaps and build validation layers to ensure accuracy, completeness, and consistency.

Documentation & Governance Maintain thorough, up-to-date documentation for all models, sources, and metrics within the dbt project.

Contribute to a governed semantic layer that provides consistent metric definitions across BI tools and stakeholders.

Support data cataloging efforts so business users can discover, understand, and trust the data they consume.

Partner with stakeholders to define and document data ownership, lineage, and access policies.

Analytics Enablement & Collaboration Partner with analysts and business stakeholders to understand reporting needs and translate them into scalable data models.

Enable self-service analytics by building intuitive, well-documented datasets that reduce ad-hoc data requests.

Support the creation of dashboards and reports in BI tools (e.g., Tableau, Power BI) by ensuring a reli...