Senior QA / Reconciliation Analyst

Job Description

Role Summary Senior QA and data-validation role focused on ETL testing, large-scale data reconciliation, regulatory-output validation, and root-cause analysis for AWS Databricks data pipelines. Roles & Responsibilities Define and execute test strategies for complex ETL / ELT pipelines and regulatory data outputs. Perform record-count, control-total, field-level, segment-level, and file-level reconciliation. Validate source-to-target mappings, transformation rules, crosswalks, defaults, and exception logic. Create test scenarios for full-refresh, incremental, historical, rerun, and error-handling scenarios. Validate data-quality rule results, failure outputs, thresholds, and remediation behavior. Build reusable SQL/Python reconciliation queries and automated regression checks where practical. Perform root-cause analysis and work with engineering and mapping teams to resolve defects. Maintain test evidence, defect logs, reconciliation results, and sign-off documentation. Support parallel comparison between legacy and modernized outputs. Required Skills & Experience 6+ years of QA, ETL testing, data validation, or reconciliation experience. Strong SQL and hands-on experience validating large datasets. Experience testing AWS Databricks, Spark, Delta Lake, or comparable cloud data-platform pipelines. Strong experience with ETL / ELT testing, data reconciliation, control totals, field-level comparisons, and batch validation. Ability to interpret source-to-target mappings, data models, and business rules. Experience with automated data testing using SQL, Python, PySpark, or test frameworks is preferred. Experience with defect triage, root-cause analysis, and test-evidence documentation. Familiarity with Git / CI/CD and data-quality frameworks is preferred. Strong analytical and communication skills. Domain Knowledge Healthcare payer / Medicaid / MMIS testing experience is preferred. T-MSIS or other regulatory-reporting validation experience is highly desirable. Understanding of CMS-style validation rules and healthcare claims, eligibility, provider, managed care, and pharmacy data. Experience validating regulatory file outputs, data-quality exceptions, and reconciliation results.