Senior Quality Engineer

Key Responsibilities:


Data Validation & QA:
• Write advanced SQL to validate transformations, joins, aggregations, and business rules across datasets and features.
• Create test plans and acceptance criteria for new data products, features, and model outputs.
Automated Testing & Quality Gates:
• Implement automated data tests (schema, freshness, distribution, reconciliation) using Python and/or data quality frameworks.
• Integrate QA checks into CI/CD pipelines and enforce release quality gates.
Monitoring & Issue Management:
• Set up monitoring for data anomalies and pipeline failures; triage issues and drive root-cause analysis.
• Partner with data engineering and ML Ops to improve observability and reduce recurrence.
Documentation & Governance:
• Document test coverage, known limitations, and lineage; support audits and compliance requirements.
• Promote best practices for data definitions and metric consistency.

Technical Qualifications Needed:

Education:

Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.

Mandatory

Required skills:

• 5+ years of experience in SQL engineering, analytics QA, or data quality roles.
• Expert SQL skills including window functions, complex joins, and performance tuning.
•

Experience with automated testing (Python/pytest) and data quality approaches.
• Familiarity with lake house/warehouse platforms (Azure SQL/Synapse/Databricks/Snowflake).
• Strong problem-solving and communication skills; ability to work across technical and business teams.
Desired

Skills:

•

Experience with Great Expectations, dbt tests, or similar quality frameworks.
• Knowledge of ML workflows and validation of model outputs (stability, drift, bias indicators).
• Experience building dashboards for data health and QA coverage.
Certifications
Relevant certifications (e.g., Azure Data Fundamentals, ISTQB) preferred.