Quality Engineer Principal - Big Data / Hadoop / Data Warehousing

Fairygodboss; Strongsville (OH); On-site; USD 140,000 - 170,000; Full time

Job summary

PNC is seeking a Quality Engineer Principal to lead enterprise-wide quality engineering for Big Data, Hadoop, and Data Warehouse platforms. Based in Pittsburgh, PA or Strongsville, OH, you will drive test strategy, automation architecture, and quality governance across onsite-offshore teams.

The role requires hands-on Python development, experience with Spark/PySpark, HQL/SQL, and Cloud environments (AWS). You will guide a 3-5 member QA team and shape SDLC/STLC practices for high-quality

Qualifications

• Extensive experience in Quality Assurance, Test Architecture, or Quality Engineering roles.
• Strong knowledge of SDLC and STLC methodologies across enterprise environments.
• Proven experience leading teams of 3-5 members in onsite-offshore delivery models.

Responsibilities

• Define and implement QA architecture, test strategies, and quality frameworks for Big Data, Hadoop, and Data Warehouse applications.
• 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.

Skills

Quality Assurance

Test Architecture

Python

Big Data / Hadoop

Data Warehouse

Spark

PySpark

HQL

SQL

AWS / Cloud Platforms

CI/CD

Agile/Scrum

DevOps

Education

Bachelor's

Tools

Hive

HDFS

YARN

Job description

Position Overview

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(n) [position title] within PNC's [name of division] organization, you will be based in [city/state location of position].

Job Profile

Position Overview

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 Engineer Principal within PNC's Data and Automation organization, you will be based in Pittsburgh, PA or Strongsville, OH.

We are seeking an experienced Quality Engineer Principal 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 DevOps practices with a quality-first mindset.

Qualifications

• 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.

Preferred Skills

• Experience with Hadoop ecosystem tools such as Hive, HDFS, YARN, and related technologies.
• Exposure to data quality frameworks and metadata validation tools.
• Experience with performance and scalability testing for distributed data platforms.
• Knowledge of Agile, DevOps, and Continuous Testing practices.
• Familiarity with data governance, data lineage, and compliance controls.
• Relevant QA, Cloud, or Big Data certifications are a plus.

Technical Skills

Core Technologies

• Python
• Big Data / Hadoop
• Data Warehouse
• Spark
• PySpark
• HQL
• SQL
• AWS / Cloud Platforms

Quality Engineering

• Test Automation
• ETL Testing
• Data Validation Testing
• API Testing
• Functional Testing
• Integration Testing
• Regression Testing
• Performance Testing

Methodologies

• SDLC
• STLC
• Agile/Scrum
• DevOps
• CI/CD

This role is ideal for a senior-quality professional who can combine test architecture leadership, deep data-platform expertise, and hands-on Python development skills to drive quality across complex enterprise data ecosystems.

PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals.

PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.

Job Description

• Drives the development of test strategies and plans, ensuring alignment with enterprise-level objectives and delivery timelines.
• Escalates systematic issues to Quality Engineer leadership and influences resolution strategies.
• Oversees risk and defect processes, ensuring adherence to ECO standards. Provides detailed insights through accurate and timely reporting.
• Leads preparation and delivery of test summary reports and documentation for Technology leaders, Governance/Risk teams, and business stakeholders.
• Collaborates across teams and participates in Quality Engineer CoP meetings to support continuous improvement and knowledge sharing.
• Provides strategic mentorship and oversight to more junior Quality Engineer team members, ensuring consistent execution of testing standards.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

• Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
• Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.

Qualifications

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Listed below are skills, competencies, work experience, education, and required certifications/licensures needed to be successful in this position.

Preferred Skills

Apache Hadoop, Big Data, Competitive Advantages, Customer Solutions, Data Warehousing (DW), Design, Enterprise Architecture Framework, Machine Learning (ML), PySpark, Risk Assessments, Technical Knowledge

Competencies

Application Testing, Coaching Others, Influencing, Process Management, Software Development Life Cycle, Software Quality Assurance And Testing, System Testing, Technical Documentation Management, Technical Troubleshooting

Work Experience

Roles at this level typically require a university / college degree, with 5+ years of industry-relevant experience. Specific certifications are often required. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Education

Bachelors