Axos Business Center, Corp
About This Job
The QA Automation Engineer is responsible for writing code to automatically test various areas of Axos core functionality, including Web UI, SQL databases, REST APIs, and Mobile devices.
Job Description
Perform quality assurance and quality control duties for the Enterprise Data Management and data development life cycle
Define, prepare, execute and implement data validation and unit and integration testing methods to ensure data quality
Contribute to the overall test strategy and quality of the data in the Databricks Lakehouse (Enterprise Data Warehouse) and develop automated/manual test procedures
Document bugs for developer review as well as provide supporting test results to assess the overall quality for the data product deliverable
Work with end users, business analysts, project managers, IT, database and Tableau developers, and data architects to understand user requirements, project milestones and scope for data integration and data fulfillment initiatives to develop comprehensive test plans
Validate technical specifications against finished data products
Design and develop test strategies that will optimize data testing cycles and provide faster throughput without compromising on data quality
Perform integration testing, regression testing, source to target testing and support periodic quantitative and qualitative data audits on post production data sets across Bronze, Silver, and Gold Delta Lake layers
Define system performance standards, establish key and ancillary performance measurements, and help to ensure platform scalability
Serve as gatekeeper for data deployments between environments and assist in automating deployments where applicable
Validate data pipelines built with PySpark/Spark SQL and Databricks Workflows/Jobs, including notebook-based ETL/ELT processes, ensuring data accuracy across Bronze, Silver, and Gold Delta Lake layers
Support validation of Unity Catalog access controls, data lineage, and governance policies to ensure secure, well-governed data access across the Databricks platform
Lead specific aspects of Data Governance and Data Quality to establish data quality rules and develop data validation tests
Leverage AI/LLM-powered tools (e.g., Claude, Copilot) to accelerate test case generation, synthetic test data creation, and code/query review, while validating AI-assisted outputs for accuracy before use in production test cycles
Utilize Agile methodologies; participate in daily scrums, testing, code reviews, build release and other weekly meetings
Join stakeholder meetings to communicate status, give demos, provide timelines and offer insights
Required Key Knowledge Skills/ Experience
2+ years' experience in QA testing, preferably in a data engineering or data warehousing environment
Data testing in SQL, PySpark/Spark SQL, and Python framework, with hands-on experience testing Databricks notebooks, Delta Lake tables, and Databricks Workflows/Jobs
Excellent verbal and written communication skills, including ability to simplify complex concepts for technical and non-technical audience
Superior problem-solving skills, self-motivation, and the capacity to work under pressure and on tight deadlines
Demonstrated ability to learn, acquire and utilize new technologies, disciplines, and frameworks as needed
Ability to build and test reliable data ETL/ELT pipelines, including Spark-based pipelines, query optimization, and dynamic SQL
Familiarity with the medallion architecture (Bronze/Silver/Gold) and Delta Lake table validation techniques, such as schema enforcement, time travel, and ACID transactions
Strong customer focus, excellent problem solving and analytical skills
Ability to work independently under minimal supervision and strong track record of setting and meeting delivery commitments
Familiarity with Agile/Scrum methodologies or working in an Agile/Scrum environment
Databricks certification (e.g., Databricks Certified Data Engineer Associate or…