QA Engineer - Data (m/f/d)

We are looking for a Data QA Engineer to join our team in ensuring the reliability, accuracy, and compliance of our Azure-based data ecosystem. You will validate data pipelines, transformations, and outputs that support patient care analytics, clinical decision tools, telehealth insights, claims processing, EHR integrations, and AI-driven health predictions.Key ResponsibilitiesDevelop and execute test strategies, plans, cases, and automated scripts for Azure data pipelines (ETL/ELT), data lakes, warehouses, and analytics layers.Validate end-to-end data flows: source ingestion → bronze/silver/gold layers (Medallion architecture) → downstream BI/ML models, ensuring accuracy, completeness, consistency, timeliness, and validity.Write complex SQL queries and Python to perform data reconciliation, profiling, anomaly detection, duplication checks, schema enforcement, and business rule validation.Build and maintain automated data quality tests using frameworks like Great Expectations, dbt tests, custom scripts, or Azure-native capabilities; integrate into CI/CD pipelines (e.g., Azure DevOps).Test Azure services including Azure Data Factory (pipelines/orchestration), Azure Databricks (Spark transformations), Azure Synapse Analytics (SQL pools, Spark pools), Azure Data Lake Storage Gen2 (ADLS), Azure Delta Lake, and integrations like Azure Health Data Services or FHIR APIs.Perform regression, integration, and performance testing on data transformations after code changes, new sources (e.g., HL7/FHIR feeds, wearables, claims data), or schema updates.Monitor production pipelines for data drifts, quality degradation, or anomalies using Azure Monitor, alerts, and logging; investigate root causes and collaborate on fixes.Ensure strict compliance with HIPAA, GDPR, HITECH, and other regulations: validate PHI handling, encryption (at rest/in transit), de-identification,Collaborate with data engineers, analysts, clinical/product teams to translate healthcare business rules (e.g., ICD-10/CPT validation, patient matching) into testable assertions and quality thresholds.Document defects, test coverage, data lineage issues, and quality KPIs; contribute to dashboards in Azure Synapse or Power BI.Participate in Agile processes (sprints, stand-ups) and advocate for “shift-left” quality in Azure data workflows.#J-18808-Ljbffr