Quality Assurance Architect - Hadoop​/Big Data​/Python

Quality Assurance Architect

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company's success. As a Quality Assurance Architect within PNC's Data and Automation organization, you will be based in Pittsburgh, PA or Strongsville, OH.

We are seeking an experienced Quality Assurance Architect to lead the design, implementation, and continuous improvement of enterprise-wide quality engineering practices for large-scale Big Data, Hadoop, and Data Warehouse platforms. This role will drive test strategy, automation architecture, and quality governance across complex data ecosystems while collaborating with cross-functional teams in an onsite-offshore delivery model.

The ideal candidate brings strong expertise in SDLC and STLC processes, hands-on technical knowledge of Python, Big Data technologies, Spark/PySpark, HQL/SQL, and experience working within AWS/Cloud environments.

Key Responsibilities:

• Define and implement QA architecture, test strategies, and quality frameworks for Big Data, Hadoop, and Data Warehouse applications.
• Establish best practices across the Software Development Life Cycle (SDLC) and Software Testing Life Cycle (STLC).
• Lead a team of 3–5 QA engineers, providing technical guidance, mentoring, and performance oversight.
• Coordinate delivery across onsite and offshore teams, ensuring effective communication, planning, and execution.
• Design and implement scalable test automation solutions for data ingestion, transformation, processing, and reporting systems.
• Develop and maintain automated validation frameworks using Python and related technologies.
• Collaborate with Architects, Product Owners, Developers, Data Engineers, and Business stakeholders to ensure high-quality releases.
• Create test strategies covering functional, integration, regression, performance, ETL, data validation, and end-to-end testing.
• Validate data pipelines and large datasets across Hadoop, Spark, Data Warehouse, and Cloud platforms.
• Perform root cause analysis of defects and drive continuous quality improvements.
• Define quality metrics, reporting mechanisms, and release readiness criteria.
• Support Agile, Scrum, and Dev Ops practices with a quality-first mindset.

Qualifications:

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.

Extensive experience in Quality Assurance, Test Architecture, or Quality Engineering roles.

Strong knowledge of SDLC and STLC methodologies across enterprise application environments.

Proven experience leading teams of 3–5 members in onsite-offshore delivery models.

Strong hands-on development and automation experience using Python.

Experience testing and validating solutions built on Big Data/Hadoop ecosystems.

Strong expertise in Data Warehouse and ETL testing.

Experience working with Apache Spark and PySpark environments.

Proficiency in HQL and SQL for complex data validation and analysis.

Experience working with AWS or other cloud platforms.

Knowledge of CI/CD pipelines and modern test automation frameworks.

Strong analytical, problem-solving, and communication skills.