Lead Quality Engineer

As a Lead Quality Engineer, you will make an impact by ensuring the highest standards of data quality, security, and compliance across our data engineering initiatives. You will be a valued member of the team and work collaboratively with managers, primary teams, and other stakeholders.

In this role, you will:

• Develop and document test plans and test cases based on software requirements and technical specifications.

• Understand, plan, and execute testing for data projects in the Databricks environment.

• Validate data ingestion pipelines, data transformations, and data quality, completeness, and performance.

• Create and document SQL-based test cases to verify data transformations across the Medallion Architecture.

• Develop and maintain automation scripts for repeatable regression and data validation testing.

• Validate data access controls, role-based security, and non-public information (NPI) requirements.

• Support Unity Catalog implementation, data dictionary migration, and Delta Sharing validation.

• Identify opportunities to apply the DQx framework for data quality validation and automation.

• Collaborate with Development and Product Owners to resolve quality engineering issues.

• Provide regular communication on testing status, issues, risks, deployments, and release activities.

Work model:

US Remote; Hybrid for NY/NJ candidates highly preferred.

We strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a remote position open to qualified applicants in the United States. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

• Experience in developing and documenting test plans and test cases based on software requirements and technical specifications.

• Understanding of data projects, data ingestion pipelines, and data transformation testing in the Databricks environment.

• Designing secure, scalable, and resilient cloud data solutions using AWS and Databricks within a hybrid work model.

• Strong SQL skills for validating data transformations and documenting verification queries.

• Experience with test automation strategies, regression testing, and data quality validation.

• Knowledge of data access controls, Unity Catalog, Delta Sharing, and data governance concepts.

These will help you stand out

• Demonstrated ability to suppo