Data Engineer Senior - Big Data Platform Team

PNC Bank•Denver, CO

15h•Onsite

About The Position

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. 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 Designs, develops and optimizes data warehouses, with flexible and scalable data and ETL architecture, to support business users and Business Intelligence (BI) applications. Analyzes business intelligence data and makes recommendations for data warehouse growth and integration an application/business function. Works with IT and business customers to capture requirements for designing the data warehouse architecture. Provides support and technical guidance to ensure the solutions are aligned with the architecture and framework. Leads and consults on the implementation and integration of data warehouses; ensures the solution meets organizational quality and integrity standards. 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

5+ years of industry-relevant experience.
Experience with Spark, SQL, and distributed data platforms.
Experience building ETL/ELT frameworks.
Experience with containerized environments (Docker, Kubernetes/OCP).
Experience with object storage platforms (e.g., S3, ADLS, or equivalent).
Experience with modern table formats such as Apache Iceberg.
Experience with CI/CD pipelines (e.g., Jenkins, GitHub/Bitbucket, Azure DevOps).
Experience with infrastructure-as-code practices.
Experience optimizing Spark jobs.
Experience with data architecture decisions, including data modeling and pipeline design.
Experience supporting migration and modernization efforts.
Experience partnering with business stakeholders and product teams.
Experience providing technical leadership and mentoring junior engineers.
Experience ensuring adherence to enterprise data governance, security, and compliance standards.
Experience following change management (CR), code review, and deployment processes.
Experience maintaining technical documentation.
Knowledge of customer needs and satisfaction.
Knowledge of risk assessment and management within business objectives.

Nice To Haves

Big Data Architecture
Machine Learning (ML)
Project Management
Quality Assurance (QA)
Risk Assessments
Technical Knowledge
Consulting
Database Structures
Data Warehousing
IT Architecture
Logical Data Modeling
Organizational Leadership
Problem Solving
Requirements Analysis

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.
Designs, develops and optimizes data warehouses, with flexible and scalable data and ETL architecture, to support business users and Business Intelligence (BI) applications.
Analyzes business intelligence data and makes recommendations for data warehouse growth and integration an application/business function.
Works with IT and business customers to capture requirements for designing the data warehouse architecture.
Provides support and technical guidance to ensure the solutions are aligned with the architecture and framework.
Leads and consults on the implementation and integration of data warehouses; ensures the solution meets organizational quality and integrity standards.

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