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.
