Data QA Engineer​/Analyst

Data QA Engineer/Analyst

We are seeking a Data QA Engineer with a meticulous eye for detail, strong analytical thinking, and a passion for data quality. In this role, you will play a critical part in ensuring the accuracy, reliability, and performance of our data pipelines and software solutions. You will collaborate closely with cross‑functional teams to validate data flows, automate testing processes, and uphold the highest standards of data integrity.

You will use your strong Python & SQL skills to provide valuable insights and support data‑driven decision‑making.

• Collaborate with Application, Data Development, Business Analysts, and Operations teams to design and implement comprehensive testing strategies.
• Review business requirements, functional specifications, and design documents to create detailed test plans.
• Design, develop, and maintain automated test cases for ETL pipelines using tools such as Validatar, Query Surge, or ICEDQ. This role will be working in a similar tool for a significant portion of their time.
• Automate data testing processes wherever feasible, including large datasets within SQL Server databases or similar.
• Perform end‑to‑end ETL validation and testing in AWS data pipelines (Glue, Athena, S3, Redshift, RDS).
• Develop and execute tests using Python or PySpark to validate large‑scale data processing jobs.
• Conduct API testing for data services and backend systems.
• Validate source‑to‑destination data movement and transformation in database applications.
• Perform backend database testing aligned with application flow functionality.
• Test BI reports and dashboards developed in Tableau.
• Assess and produce Key Performance Indicators (KPIs) for Imaging (DICOM) and clinical data ingestion pipelines.
• Participate in design and SQL code reviews to ensure testability and adherence to quality standards.
• Plan and execute Manual, Functional, and Regression test suites.
• Assist in QA discovery or analysis to identify gaps and facilitate requirements refinement.

• Bachelor's degree in Health Informatics, Computer Science, or a related field.
• 3–5 years of experience in Test Strategy, Test Design, Execution, and Reporting.
• 3+ years writing Python and/or PySpark in a Production environment.
• 2+ years of expert‑level experience in testing and automating large datasets within SQL Server databases or similar.
• Strong proficiency in writing complex SQL queries, stored procedures, functions, views, and indexes.
• In-depth knowledge of developing SQL scripts using functions, grouping operations, subqueries, analytical functions, and joins for ETL testing.
• Strong understanding of ETL concepts and AWS data flow diagrams.
• Experience in testing database applications for data movement and transformation.
• Experience with AWS Glue, Athena, S3, Redshift, and RDS.
• Proficiency in Python, API testing, and test automation frameworks.
• Familiarity with Git Hub and Azure Dev Ops.
• Knowledge of HL7, DICOM, and HIPAA standards and interoperability.
• Strong communication skills and experience working in Agile environments.

Data QA, Data Quality, SQL, ETL Testing, Python, HL7, DICOM, Health Informatics, AWS Glue, Athena, S3, Redshift, Tableau, API Testing, Automation, Agile, Validatar, Query Surge, ICEDQ