Position: Quality Assurance Lead – Data and Automation, Enterprise Data Analytics. Location: Pittsburgh, PA or Cleveland, OH. Work arrangement: On-site. Overview: As a Quality Assurance Lead within PNC's Enterprise Data Analytics organization, you will develop data warehouse testing strategies, test plans, and test cases for data warehouses and decision-support systems. You should have strong knowledge of Hadoop, HQL/SQL, PySpark, RDBMS, AWS, and data warehouse testing; Python and data development knowledge is a plus. You will review data quality, data loads, transformations, extractions, and merges loaded by ETL jobs from legacy systems into relational databases. You will participate in large-scale Enterprise Data Warehouse, Data Integration, Data Migration, and upgrade projects. You will work with GIT, JIRA, Jenkins and have a solid understanding of HTTP, JSON APIs. Responsibilities: Lead the review of testing artifacts throughout the product life cycle to ensure sign-off and prioritize testing work. Coordinate test strategy, scripting, and defect resolution. Ensure early engagement with internal partners and proactive planning to place quality at the forefront of the product lifecycle. Take accountability for quality standards, test scripts, and opportunities for automation. Develop meaningful management metrics to gauge project health and identify trends for continuous improvement in product releases. Qualifications: 3+ years of relevant experience. Bachelor's degree typically required; certifications often desired. Preferred skills include analytical thinking, QA and t

Position: Quality Assurance Lead – Data and Automation, Enterprise Data Analytics. Location: Pittsburgh, PA or Cleveland, OH. Work arrangement: On-site. Overview: As a Quality Assurance Lead within PNC's Enterprise Data Analytics organization, you will develop data warehouse testing strategies, test plans, and test cases for data warehouses and decision-support systems. You should have strong knowledge of Hadoop, HQL/SQL, PySpark, RDBMS, AWS, and data warehouse testing; Python and data development knowledge is a plus. You will review data quality, data loads, transformations, extractions, and merges loaded by ETL jobs from legacy systems into relational databases. You will participate in large-scale Enterprise Data Warehouse, Data Integration, Data Migration, and upgrade projects. You will work with GIT, JIRA, Jenkins and have a solid understanding of HTTP, JSON APIs. Responsibilities: Lead the review of testing artifacts throughout the product life cycle to ensure sign-off and prioritize testing work. Coordinate test strategy, scripting, and defect resolution. Ensure early engagement with internal partners and proactive planning to place quality at the forefront of the product lifecycle. Take accountability for quality standards, test scripts, and opportunities for automation. Develop meaningful management metrics to gauge project health and identify trends for continuous improvement in product releases. Qualifications: 3+ years of relevant experience. Bachelor's degree typically required; certifications often desired. Preferred skills include analytical thinking, QA and t