Senior Data Engineer - Hadoop/Spark/OCP/Big Data

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 Data Engineer Senior within PNC's Data Products organization, you will be based in Pittsburgh, PA, Dallas, TX, Birmingham, AL, Strongsville, OH, Denver, CO, or Phoenix, AZ.

Due to the nature of the position, we are looking for Data Engineers with the following experience:

Data Pipeline Development & Engineering - Design, develop, and maintain scalable data pipelines using Spark, SQL, and distributed data platforms. - Build robust ETL/ELT frameworks supporting batch and real-time processing. - Ensure code quality, modularity, and reusability across pipelines.

Platform, Containerization & Infrastructure - Work with containerized environments (Docker, Kubernetes/OCP) to deploy and manage data workloads. - Support containerization initiatives for Spark workloads and platform modernization. - Collaborate with infrastructure teams for resource allocation, scaling, and cluster optimization.

Object Storage & Data Lake Technologies - Design and manage data on object storage platforms (e.g., S3, ADLS, or equivalent). - Implement and optimize modern table formats such as Apache Iceberg for large-scale analytics. - Ensure efficient data partitioning, versioning, and lifecycle management in data lakes.

DevOps & CI/CD Practices - Implement and maintain CI/CD pipelines for data engineering workflows (e.g., Jenkins, GitHub/Bitbucket, Azure DevOps). - Automate deployments, testing, and monitoring of data pipelines. - Support infrastructure-as-code practices and environment standardization. 5. Resource Utilization & Performance Optimization - Optimize Spark jobs for performance, memory, and compute efficiency. - Monitor resource allocation (CPU, memory, storage) and drive improvements. - Identify and resolve bottlenecks in distributed processing environments.

Architecture & Solution Design - Contribute to data architecture decisions, including data modeling and pipeline design. - Support migration and modernization efforts (e.g., legacy to cloud/OCP platforms). - Evaluate and recommend new technologies for scalability and efficiency.

Collaboration & Leadership - Partner with business stakeholders and product teams to define data requirements. - Provide technical leadership and mentor junior engineers. - Participate in sprint planning, design reviews, and release governance.

Governance & Compliance - Ensure adherence to enterprise data governance, security, and compliance standards. - Follow change management (CR), code review, and deployment processes. - Support audit readiness and vulnerability remediation activities.

Documentation & Knowledge Sharing - Maintain clear technical documentation for pipelines and architecture. - Conduct KT sessions and support onboarding/offboarding activities. - Promote engineering best practices across the team.

- Leads in developing, supporting and implementing data solutions for multiple applications in order to meet business objectives and user requirements. Leverages technical knowledge and industry experience to design, build and maintain technology solutions. - Leads data requirement analysis and the data preparation process development for targeted data solutions. - Leads in designing and building data service infrastructure on multiple data platforms, according the workflow. - Oversees the development and implementation of data solutions for multiple applications to ensure its scalability, availability and maintainability. - Consults on data migration and transformation to ensure the accuracy and security of data solutions.

Preferred Skills Analytical Thinking, Competitive Advantages, Data Analytics, Data Mining, Data Science, Machine Learning (ML)

Competencies Application Delivery Process, Big Data Management and Analytics, Business Intelligence, Consulting, Data Analysis - Software, Data Architecture, Database Structures, Problem Solving, Software Development Life Cycle

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.

Generally, this opening is expected to be posted for two business days from 07/15/2026, although it may be longer with business discretion.