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 Data Engineer within PNC's Technology organization, you will be based in Pittsburgh, PA, Dallas, TX, Cleveland OH or Birmingham, AL.

We are seeking a Data Engineer to help support large-scale enterprise big data platforms. This team is responsible for building and evolving modern data solutions that enable analytics across the organization while partnering closely with business stakeholders.
Ideal candidates thrive in problem-solving environments, help shape analytical solutions, and contribute to the design of a next-generation, cloud-native data platform.

Key Responsibilities:

• Monitor, maintain, and improve the health and performance of the data platform
• Ensure stability, reliability, and scalability of data systems
• Implement best practices for platform operations and data engineering standards. Ensure understanding and adherence across technical and business customers
• Perform frequent reviews of the data platform architecture and identify areas for automation, optimization, right-sizing, and cost reduction to support health of the environment
• Contribute to large-scale transformation initiatives, including:
○ Driving user migration to a unified data platform
○ Modernizing legacy Hadoop-based systems to cloud-native architectures
• Design and build scalable, modern data platforms leveraging:
○ Open-source technologies such as Apache Iceberg, Airflow, and Trino
○ Data lakehouse architecture for structured, transactional data availability
• Partner with business stakeholders to translate analytical needs into technical solutions
○ Apply modern principles, methodologies and tools to advance business initiatives and capabilities
• Act as an internal consultant to internal customers on big data tools and capabilities
○ Enhance and optimize query performance and data structures to support analytical
○ Guide stakeholders in understanding how to leverage data for business insights
• Define and implement internal process improvements through the development of detailed analytics that provide actionable insights into key business performance metrics

Key Skills and Experience:

• Strong proficiency in relevant programming languages such as Python, Spark, Scala
• Strong background and practical experience in SQL development and enterprise database systems (Oracle, Teradata, etc.)
• Experience with modern, cloud-native and open-source tools is highly valued:
○ Apache Iceberg
○ Apache Airflow
○ Trino
• Strong experience in modern data engineering and big data ecosystems / frameworks
• Hands-on experience building scalable data platforms and analytical solutions using data lakehouse architectures
• Familiarity with cloud platforms (e.g Azure , AWS ) and their data related services
• Proven ability to go beyond data movement and contribute to solution design
• Strong communication and presence — able to translate between technical and non-technical audiences
• Proven ability to bridge the gap between business and engineering teams
• Collaborative mindset with experience working across cross-functional teams
• Strong problem-solving and critical thinking skills

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

• Develops, supports and implements data services for multiple applications to meet business objectives and user requirements. Uses technical knowledge and industry experience to design, build and maintain technology solutions.
• Works closely with users, developers, operations and business partners to define data service requirements and the data preparation process development.
• Designs and builds data service infrastructure on multiple data platforms, according to key business processes and the overall workflow.
• Develops and implements data solutions for multiple ap