Expert, Data Engineering

As a Data Specialist, you will ensure that data used in AI projects is reliable, well-structured, and compliant with governance standards.

You will engage with stakeholders to ensure use case data is usable, trustworthy, and traceable, enabling the development of high-quality AI tools that improve internal efficiency and automate workflows.

You will also establish data standards to improve data governance and data quality for AI projects.

Job's Responsibilities

1

Acquire and Prepare Internal Data for AI Initiatives- Engage with stakeholders to identify and collect data from diverse internal sources, including databases, file systems, and application logs.
- Clean and preprocess raw data to remove noise, handle missing values, and ensure consistency.

- Perform data labeling and annotation to create high-quality datasets for training and evaluation.
- Architect, build, and maintain reliable ETL/ELT pipelines to automate the ingestion, cleaning, and transformation of data from diverse internal sources (databases, applications, logs, documents).

2

Co-Management & Ingestion of Knowledge Bases for AI-Powered Tools- Collaborate with SMEs to manage & ingest Knowledge Bases for AI-Powered Tools.

- Collaborate with LLM engineers to optimize embedding strategies and retrieval performance.
- Monitor and maintain the health, accuracy, and freshness of knowledge bases.
- Implement access controls and data governance policies for sensitive internal information.

3

Own Data Quality, Governance and Compliance Across AI Projects- Establish and champion data quality standards, metrics, and monitoring dashboards to proactively identify and resolve data issues.
- Develop and implement data validation frameworks, ensuring the fitness of data for training, evaluation, and inference throughout the AI lifecycle.
- Work with legal and compliance teams to ensure AI projects adhere to data privacy regulations.
- Conduct regular audits of data usage and storage to identify and mitigate risks.

4

Support Data Analysis and Insight Generation for Stakeholders- Develop interactive dashboards and reports using tools like Tableau or Power BI.
- Collaborate with AI engineers to define data requirements and success metrics for models.

- Monitor & present data findings from AI projects to stakeholders in a clear, actionable, and visually compelling manner.

5

Collaborate Cross-Functionally to Enable Data-Driven Decision Making- Act as the primary data liaison between AI engineers, business stakeholders, and platform teams, translating data requirements and constraints.
- Create and maintain comprehensive data documentation to ensure clarity and reproducibility.
- Train and support business users on data tools, self-service analytics, and data literacy.
- Contribute to the design and implementation of data infrastructure and architecture.

Qualifications and Experience

1.

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related fields

2.

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