Senior QA Engineer – Data (Databricks)
About the Role
The Senior QA Engineer for Data will test and validate the data platform behind our internal back-office systems, including Databricks pipelines and the Power BI reports that business users rely on. This is a hands-on senior role: you'll make sure our data is accurate, complete, and timely, build automated data tests, and mentor onshore and nearshore QA testers. You'll partner closely with data engineers and business stakeholders and work within an agile environment.
Responsibilities
- Design and carry out test strategies for data pipelines built in Databricks, covering ingestion, transformation, and output.
- Validate data accuracy, completeness, and consistency between sources and targets, including reconciliation and data comparison processes.
- Build and maintain automated data tests in Python and Pytest, using SQL and PySpark to validate tables and transformations.
- Test and validate Power BI reports against source data.
- Define and implement data quality checks, and help set QA standards for the data platform.
- Integrate data tests into CI/CD pipelines.
- Investigate data defects and pipeline performance issues, and coordinate fixes with data engineering.
- Work with business users to understand how they use data and reports, and propose technical and non-technical solutions to business problems.
- Mentor onshore and nearshore QA testers, and review their test code against coding standards.
- Track and report on data quality metrics, test coverage, and release readiness.
- Stay current on QA tools and practices, including AI-assisted testing.
Required Qualifications
- 6+ years of QA experience, including 3+ years testing data pipelines, data warehouses, or analytics platforms.
- Hands-on experience testing in Databricks.
- Strong SQL skills for data validation and reconciliation.
- Proficiency in Python and Pytest.
- Experience with PySpark or Spark SQL.
- Solid understanding of ETL/ELT processes and data modeling concepts.
- Experience testing in cloud environments (Azure preferred).
- Experience with a test management tool (Qase preferred).
- Experience working in an agile environment.
- Strong process discipline and attention to detail.
- Excellent verbal and written communication skills, with a customer-service mindset toward business users.
Preferred Qualifications
- Experience testing or validating Power BI reports.
- Experience with Delta Lake and Unity Catalog.
- Experience with data quality frameworks (e.g., Great Expectations or Databricks pipeline expectations).
- Experience with CI/CD pipelines (e.g., Azure DevOps).
- Experience mentoring QA testers or working with distributed or nearshore teams.
- Familiarity with AI-assisted development tools such as Claude Code.
Current Tech Stack
Python, Pytest, SQL, PySpark, Databricks, Power BI, Qase, Azure, Claude Code
Skills Required
- 6+ years of QA experience, including 3+ years testing data pipelines, data warehouses, or analytics platforms
- Hands-on experience testing in Databricks
- Strong SQL skills for data validation and reconciliation
- Proficiency in Python and Pytest
- Experience with PySpark or Spark SQL
- Understanding of ETL/ELT processes and data modeling concepts
- Experience testing in cloud environments, preferably Azure
- Experience with a test management tool, preferably Qase
- Experience working in an agile environment
- Strong process discipline and attention to detail
- Excellent verbal and written communication skills with a customer-service mindset
- Experience testing or validating Power BI reports
- Experience with Delta Lake and Unity Catalog
- Familiarity with data quality frameworks such as Great Expectations or Databricks pipeline expectations
- Experience with CI/CD pipelines such as Azure DevOps
- Experience mentoring QA testers or working with distributed or nearshore teams
- Familiarity with AI-assisted development tools such as Claude Code
What We Do
Atlas Systems is a technology company founded in 2003 in Princeton, New Jersey, serving Fortune 1000 and mid-sized clients across healthcare, financial services, manufacturing, and other regulated industries. We build AI-powered platforms that solve operational problems most enterprises still handle manually or through legacy systems: PRIME®: A provider data management platform used across U.S. healthcare, covering payers, providers, health systems, and provider groups. PRIME keeps provider directories accurate, automates credentialing and enrollment, and helps organizations meet compliance and directory accuracy requirements. ComplyScore®: A risk and compliance management platform covering third-party risk management, continuous compliance, and internal risk domains, including a Headless TPRM offering. Used by regulated industries including healthcare, financial services, manufacturing, and life sciences across the US, EU, APAC, and India. AInfinity®: An agentic AI automation platform that applies AI to workflows across healthcare and risk and compliance. Beyond our platforms, our IT Services division works alongside client teams and systems, providing managed IT services, infrastructure support, application development, database services, cloud migration, and IT security to organizations that need dependable, hands-on technical partners. We manage 6,000+ database instances, and our platforms are built to hold up at enterprise scale: accurate enough to pass an audit or regulatory review, and simple enough that clients get more value at a lower total cost of ownership than comparable solutions. We're small enough to know our clients by name and big enough to support Fortune 1000 operations across geographies.
Why Work With Us
We're a team-first culture where people grow fast, own real problems, and see their work reach Fortune 1000 clients from day one. We promote from within and invest in ongoing development, because our platforms are only as good as the people building them.
