Data Testing Lead (Python) – QA for Data Pipelines

PNC; Pittsburgh (Allegheny County); On-site; USD 86,000 - 173,000; Full time

Benefits offered by this job

Medical/Dental/Vision

401(k) with match

Pension and stock purchase plans

Educational assistance

Wellness program

Job summary

PNC is seeking a Quality Engineer Lead - Data Testing (Python) based in Pittsburgh, PA or Strongsville, OH. You will lead test strategy for data-intensive platforms, guide junior staff, and ensure data accuracy and compliance across risk and banking domains.

The role blends manual and automated testing with Python-based automation while collaborating across teams and driving continuous QA improvements in an in-office environment.

Qualifications

• Experience testing Python-based data pipelines and APIs in data-intensive systems.
• Ability to validate data accuracy, integrity, and regulatory compliance across complex platforms.
• Experience guiding junior testers and coordinating with cross-functional teams.

Responsibilities

• Lead development and review of test strategies and plans aligned with project goals.
• Identify and address resource and environment gaps, escalating issues to QA leadership.
• Monitor risks, defects and ensure ECO-aligned reporting and resolution.
• Prepare and deliver test summary reports for Technology leaders and stakeholders.
• Collaborate across teams and participate in QA communities for continuous improvement.

Skills

Analytical Thinking

API Programming

Controls Testing

Corporate Governance

Python

Quality Assurance

Quality Support

Software Testing

Test Case Development

Usability Testing

Education

Bachelors

Job description

PNC is seeking a Quality Engineer Lead - Data Testing (Python) based in Pittsburgh, PA or Strongsville, OH. You will lead test strategy for data-intensive platforms, guide junior staff, and ensure data accuracy and compliance across risk and banking domains.

The role blends manual and automated testing with Python-based automation while collaborating across teams and driving continuous QA improvements in an in-office environment.