Description

You will lead the end-to-end data quality strategy for enterprise data products, services, and integrations.

Responsibilities

• Define and execute a comprehensive data quality testing strategy, including validation, reconciliation, and anomaly detection.
• Oversee functional, integration, regression, and performance testing for data pipelines and ETL processes.
• Implement automated data validation frameworks and integrate test automation into CI/CD/CT pipelines.
• Lead and mentor a team of data testers and QA engineers to drive testing excellence.
• Manage the resolution of data quality issues and defects through proactive monitoring.
• Ensure compliance with regulatory and security standards such as HIPAA and GDPR.

Required Skills

• 10+ years of experience in data quality testing, data validation, or data engineering QA.
• 3+ years in a leadership role.
• Expertise in data warehouse, data lake, and ETL testing on cloud-based platforms, specifically GCP BigQuery.
• Strong proficiency in SQL and Python for data validation and automation.
• Experience with data testing frameworks such as Great Expectations, dbt tests, or Deequ.
• Proven track record with test automation, CI/CD integration, and performance testing.
• Ability to define test data requirements and test beds for large-scale programs.
• Knowledge of DevOps practices and CI/CD workflows.
• Experience ensuring compliance with HIPAA and GDPR.

Preferred Skills

• Experience with healthcare data platforms and regulations including FHIR and HL7.
• Familiarity with data observability, metadata management, and governance tools like Collibra or Monte Carlo.
• Knowledge of GCP data services including Dataflow, Pub/Sub, and Cloud Storage.
• Experience in data API testing and service validation.

Key Skills

Education

Any Gradute