Lead the Data Quality Assurance (QA) function within the enterprise QA organization.
Develop, own, and mature test strategy, planning standards, and execution methodology for data pipelines and analytics outputs, aligned to ASTQB principles.
Transition Data QA from ad-hoc scripting to structured, formalized test plans and regression coverage.
Define and operationalize data quality validation checkpoints across ingestion, transformation, and delivery layers.
Establish and manage data quality validation criteria based on governance-defined dimensions: completeness, accuracy, timeliness, consistency, and uniqueness.
Oversee development and execution of formal test suites for Tier 1 and Tier 2 data pipelines.
Ensure regression coverage for data pipelines to prevent undetected quality regressions.
Collaborate with Data Engineering and Analytics teams on pipeline architecture and validation feasibility.
Manage defect tracking, severity classification, escalation, and root cause analysis for data quality issues.
Drive automation strategy for data pipeline validation, focusing on regression and contract-based testing.
Evaluate, select, and implement data QA tools (e.g., Great Expectations, dbt, Soda, Monte Carlo).
Establish and report data quality metrics, including validation coverage, defect rates, and incident trends.
Collaborate with Data Governance and Informatics to align QA activities with quality standards and ensure testable acceptance criteria.
Participate in retrospectives to identify and address upstream data quality issues.
Lead and develop QA team, including hiring, mentoring, and retaining staff.
### Required Qualifications
7+ years QA experience, with 3+ years in data quality/pipeline/analytics QA.
Proven experience maturing data QA practices (from ad-hoc to structured methodology).
Hands-on with data quality testing frameworks and tools (Great Expectations, dbt, Soda, etc.).
Strong understanding of data quality dimensions and validation rules.
Experience with cloud data platforms (Azure, AWS, GCP) and modern data stacks (Databricks, Snowflake, etc.).
Leadership experience in QA team or people management roles (2+ years).
Solid healthcare industry background and current experience.
### Preferred Qualifications
ISTQB/ASTQB certification (any level).
Experience in healthcare, specialty pharmacy, or regulated data environments.
Familiarity with data governance frameworks (DAMA-DMBOK).
Experience with pipeline observability tools (Monte Carlo, Datadog, etc.) and data contract testing.
Familiarity with Databricks medallion architecture, Unity Catalog, and Delta Lake.
Bachelor s degree in Computer Science, Information Systems, Data Engineering, or related field (or equivalent experience).
Note
Local candidates preferred; must report onsite for onboarding and occasionally (every 2-3 months).
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