Data Quality and Test Automation Engineer

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Engineering Shared Services Full Time IN

2 days ago Requisition

ELLKAY started out providing connectivity solutions to laboratories and within a few years, grew to also provide data management solutions to ambulatory organizations. ELLKAY is now a trusted data management partner in five healthcare segments. ELLKAY’s solutions continue to serve laboratories and ambulatory practices and have expanded to empower hospitals and health systems, healthcare IT vendors, ambulatory practices, health plans, and other healthcare organizations with cutting-edge technologies and solutions that drive their growth and interoperability strategies.

Today, ELLKAY remains true to our core values, building strong partner relationships and offering unparalleled service and support while providing innovative, scalable solutions to the challenges our customers face in today’s data-rich world. ELLKAY's experience, customer-focused approach, and reputation for innovation, speed, and accuracy differentiate ELLKAY as a premier partner for your interoperability needs and data management strategy.

Job Description:

Develop, execute, and maintain automated tests for healthcare data pipelines, integrations, transformations, and reporting outputs. Use SQL and Python to validate data mappings, reconcile source and target records, and identify missing, duplicate, inconsistent, or incorrectly transformed data. Work within established frameworks to provide dependable validation evidence and timely feedback on data quality.

Reporting and collaboration

Report to the Senior Manager QE Technology and Innovation and receive technical guidance from the Senior Data Quality Engineer and Principal Quality Architect. Collaborate with Data Engineering, product QEs, analysts, and the Healthcare SME to validate assigned data flows against documented business rules.

Key responsibilities

Review data requirements, source-to-target mappings, business rules, and acceptance criteria to identify test scenarios and expected results.

Develop and maintain SQL- and Python-based automated checks using approved data-testing frameworks and reusable utilities.

Validate data completeness, accuracy, consistency, timeliness, uniqueness, and referential integrity across assigned datasets.

Reconcile source and target records, counts, totals, and key attributes across ingestion, transformation, and reporting layers.

Test batch and incremental loads, schema changes, error handling, retries, and recovery scenarios under senior technical guidance.

Prepare approved synthetic or masked datasets and follow access, privacy, and sensitive healthcare data-handling procedures.

Execute data regression tests within CI/CD pipelines, analyze failures, and maintain clear validation results and test evidence.

Document reproducible data defects, collaborate with Data Engineers on investigation, and verify fixes and affected downstream outputs.

Use approved AI tools to assist with SQL, Python, test scenarios, and failure analysis while validating generated outputs and protecting sensitive data.

Maintain existing data-quality checks and alerts, contribute to code reviews, and add regression coverage for assigned production data issues.

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Experience and qualifications

3+ years in software testing, quality engineering, or data validation, including 2+ years of hands-on ETL/ELT or database testing and SQL-based validation. Experience may overlap.

Required qualifications

Bachelor's degree in computer science, engineering, information systems, or a related field, or equivalent practical experience.

3+…