Data Engineer Associate - Data Products

PNC•Pittsburgh, PA

1d•Onsite

About The Position

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 Software Engineer Associate within PNC's Data Products organization, you will be based in Pittsburgh, PA. Design, build, and maintain scalable data ingestion pipelines across on-premises and cloud environments. Develop and apply data modeling techniques to support analytics and reporting use cases. Ensure data quality, governance, security, and compliance across data domains. Collaborate with business analysts, data scientists, and other stakeholders to gather requirements and deliver reliable data solutions. Use cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark, Kafka) to develop robust data assets. Apply DevOps best practices and CI/CD tools to automate, deploy, and optimize data workflows. Implement application health monitoring and alerting to ensure data pipeline reliability and performance. Participate in Agile/SAFe ceremonies, including sprint planning, daily standups, and retrospectives. 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.

Requirements

University / college degree, with 2+ years of relevant professional experience. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.
Bachelors

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
Data Analysis - Software
Data Architecture
Database Structures
Effective Communications
Problem Solving
Software Development Life Cycle

Responsibilities

Design, build, and maintain scalable data ingestion pipelines across on-premises and cloud environments.
Develop and apply data modeling techniques to support analytics and reporting use cases.
Ensure data quality, governance, security, and compliance across data domains.
Collaborate with business analysts, data scientists, and other stakeholders to gather requirements and deliver reliable data solutions.
Use cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark, Kafka) to develop robust data assets.
Apply DevOps best practices and CI/CD tools to automate, deploy, and optimize data workflows.
Implement application health monitoring and alerting to ensure data pipeline reliability and performance.
Participate in Agile/SAFe ceremonies, including sprint planning, daily standups, and retrospectives.
Assists 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.
Performs data requirement analysis and the data preparation process development for targeted data solutions.
Assists in designing and building data service infrastructure on multiple data platforms, according the workflow.
Participates 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.