Big Data

PNC•Strongsville, OH

1d•$50,000 - $185,900•Onsite

About The Position

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. 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. 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 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. 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.

Requirements

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.
Knowledge 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.
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.

Nice To Haves

Analytical Thinking
Competitive Advantages
Data Analytics
Data Mining
Data Science
Machine Learning (ML)
Application Delivery Process
Big Data Management and Analytics
Business Intelligence
Consulting
Data Analysis - Software
Data Architecture
Database Structures
Problem Solving
Software Development Life Cycle

Responsibilities

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.
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.
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.
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.
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.
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.
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.
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.
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.

Benefits

medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service.