Role: Senior QA Automation Engineer 

Hybrid (2 days a week onsite) 3501 University Blvd E, Adelphi, MD 20783 

Local Candidates only 

USC or GC 

Interview : Not sure about interview mode so they have to be prepared for an in person they don't say ahead 

Send resume, visa, DL and make sure skills from job are all on resume 

Senior QA Automation Engineer – Enterprise Data & Analytics Platform

Role Summary:

We are seeking a highly skilled and self-directed Senior QA Engineer/SDET to drive comprehensive quality engineering for our Enterprise Data & Analytics Platform. Reporting into the Sr. Director – Analysis, Change and Quality, this role will own and implement advanced automated testing strategies across the entire data lifecycle, ensuring data reliability, data quality, and AI/BI model accuracy. This role requires deep technical expertise in automation tools to test data pipelines in data bricks and data quality frameworks. 

Key Responsibilities:

·    Architect and implement robust automated testing frameworks leveraging PySpark and Databricks-native tools for data validation across Raw, Curated, and Mart layers.

·    Design and implement data quality validation frameworks, including checks on accuracy, completeness, and consistency across transformation layers.

·    Create advanced data quality KPIs, integrating them into automated dashboards to track quality trends across layers.

·    Design metadata-driven tests, integrating with CI/CD pipelines, with coverage on all transformation layers.

·    Lead development of QA user stories and acceptance criteria, precisely defining test scenarios for ingestion, transformation, and consumption layers.

·    Perform complex data reconciliation testing across 10+ source systems, ensuring accuracy, completeness, and consistency from source through Mart.

·    Own the end-to-end testing lifecycle (QA, Staging, Production), defining what and when to test at each stage and ensuring sign-off criteria are met.

·    Partner closely with data engineers to troubleshoot pipeline failures, connectivity issues, and performance bottlenecks.

·    Set standards for data lineage and auditability, ensuring every transformation step can be validated and traced.

·    Plan, facilitate, and manage User Acceptance Testing (UAT) involving business users for data visualization tools such as Tableau running on Databricks.

·    Prepare UAT test scenarios aligned with business use cases, guide users through testing, and gather actionable feedback. 

·    Drive defect triage, resolution, and retesting, ensuring readiness for production release. 

·    Work within a SAFe Agile framework, participating in PI planning, sprint ceremonies, and cross-team coordination. Collaborate with DevOps, Data Engineers, Data Scientists, and Product Owners to integrate QA into CI/CD