Senior Data QA Engineer, Lantern

• The ideal candidate brings deep expertise in SQL, Python, and Azure-based platforms, along with a passion for ensuring data integrity across complex, multi-source environments
• Bachelor’s in Computer Science, Engineering, or related field
• 5+ years of functional QA experience in data-centric systems, with a strong focus on healthcare data
• Solid experience with SQL and test case design for validating data transformations and quality rules
• Familiarity with Azure services (Data Factory, Databricks, Data Lake, Azure Runbooks)
• Strong communication, documentation, and defect triaging skills

Desirable

• Lantern is seeking a Senior Data QA Engineer to join our Data Engineering team and drive quality across the foundations of our evolving Data Platform
• You will lead functional testing efforts for data platform modules like Observability, Lineage, Access Controls, and Parsing engines, with a strong focus on data exchanges, both ingress and egress, using healthcare industry standard formats
• Your work will help build trust in data as we scale our platform and processes
• Lead test efforts for healthcare-specific data using healthcare industry & custom data exchange standards, with a focus on validation and regulatory compliance
• Develop detailed test cases and comprehensive test scenarios, accurately estimate testing efforts, and strategically plan test activities to ensure thorough coverage and efficiency
• Perform functional and integration testing of Azure-based data pipelines, including Azure Data Factory, Databricks, and Data Lake storage
• Validate complex data transformations, lineage, and business rules across ingestion, staging, warehouse, and export layers using advanced SQL
• Collaborate with data engineers, analysts, and business stakeholders to define quality benchmarks, test strategies, and coverage
• Participate in design and code reviews to identify potential risks and ensure testability of pipeline components
• Contribute to continuous QA process improvements and support automation through Python scripting and CI/CD tools (e.g., GitHub Actions, Azure DevOps)
• Knowledge of data management concepts including ETL processes, data modeling, and data governance
• Ability to prioritize and manage multiple tasks in a fast-paced environment