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.