Job Details

Support the Data Engineering and AI Strategy teams by validating metadata ingestion outputs, analyzing lineage completeness, and creating Power BI reports that summarize lineage coverage and modernization insights for business and technical stakeholders.
Key Responsibilities:

• Analyze metadata and lineage results to detect data-flow gaps, unused or orphan tables, and anomalies.
• Perform data reconciliation between source and target systems to validate completeness and accuracy of ingestion.
• Create and maintain Power BI dashboards and reports that visualize lineage coverage, ETL health, and modernization metrics.
• Document lineage findings, data-quality issues, and remediation recommendations.
• Collaborate with Data Engineers to enhance lineage logic and with the AI Strategist on modernization insights.
• Verify deployment readiness by ensuring that ingestion logic aligns with production datasets and metadata standards.

Required Skills:

8+ years in data analysis, data operations, or metadata validation roles with proven experience in Power BI and SQL-based lineage/QA work.

• Power BI - advanced report building, DAX expressions, and data-model creation.
• SQL - strong query writing, joins, aggregations, and set-based validation logic.
• Excel / Python (pandas) - for ad-hoc analysis, lineage comparison, and quick statistical validation.
• Understanding of ETL flows (Informatica, AWS Glue, Azure Data Factory) and job scheduling dependencies.
• Metadata / lineage tools - exposure to Collibra, Alation, or custom metadata repositories.
• Data documentation and QA discipline - ability to trace and explain data-flow logic clearly.

Nice to Have:

• Familiarity with AWS Glue Catalog, Azure Synapse, or BladeBridge lineage outputs.
• Knowledge of Client Batch Processing concepts.
• Exposure to data-modernization or cloud migration initiatives.