Data Quality Analyst

Role Summary

Lead efforts to implement new Data Quality standards, emphasizing on modernizing existing ETL pipelines with reusable engineering patterns for implementing Data quality in a "shift left" approach.

Required Skills

Strong ETL/ELT and data engineering experience (Datastage, DBT, Informatica, Snowflake)

Strong SQL + Python skills

Hands-on Data Quality engineering experience

Experience embedding automated DQ checks into pipelines

Strong CI/CD and automated testing knowledge

Understanding of shift-left/inline DQ architecture

Experience designing reusable, scalable pipeline/DQ patterns

Technical leadership and ability to drive adoption across engineering teams

Key Deliverables

DQ-Enabled ETL Pipelines

Implement DQ checks across priority ETL pipelines

Incorporate completeness, validity, accuracy, consistency, uniqueness, and reconciliation checks

Determine appropriate DQ checkpoints throughout the pipeline

Automated DQ Testing & CI/CD Integration

Integrate DQ validation into automated pipeline testing and CI/CD processes

Establish quality gates and thresholds for pipeline promotion

Automate execution and reporting of DQ tests

DQ Failure & Exception Handling

Implement standardized approaches for handling DQ failures

Define reject, quarantine, warning, and pipeline-stop patterns

Enable automated alerting and issue routing

DQ Monitoring & Reporting

Implement monitoring of DQ results within ETL pipelines

Provide visibility into DQ failures, trends, and recurring issues

Capture DQ results and metadata for downstream reporting and governance