Data Engineer-ETL| Informatica | SQL PL/SQL | RDBMS | Data Warehousing

PNC•Pittsburgh, PA

19h•Onsite

About The Position

At PNC, the Data Engineer will be a key member of the Technology organization, based in Pittsburgh, PA. This role is crucial for developing, supporting, and implementing data services across multiple applications to meet business objectives and user requirements. The Data Engineer will leverage technical knowledge and industry experience to design, build, and maintain robust technology solutions. This involves close collaboration with users, developers, operations, and business partners to define data service requirements and develop data preparation processes. The position also entails designing and building data service infrastructure on various data platforms, ensuring scalability, availability, and maintainability of data solutions, and implementing data migration and transformation activities to guarantee data accuracy and security. PNC fosters an inclusive, in-office workplace culture that values employees and encourages their contribution to the company's success.

Requirements

Strong experience in data engineering and ETL development
Strong experience with Informatica (PowerCenter and/or Informatica Cloud/IICS)
Advanced SQL, PL/SQL skills and experience with large-scale data transformations
Experience with data warehousing platforms (e.g. SQL Server, Oracle, Teradata)
Writing and optimizing code for data pipelines to ensure systems are highly efficient, scalable, and capable of handling large-scale financial datasets.
Proficient with code deployment tools such as Udeploy, Artifactory
Experience with cloud data platforms (Azure, AWS, or GCP)
Knowledge of financial and cost data, preferably Activity Based Costing
Experience with data quality, reconciliation, and performance optimization
Excellent problem-solving and collaboration skills
Familiarity with Agile/Scrum development environments
Strong collaboration and communication skills for working with finance and business stakeholders
Excellent communication skills, with the ability to present insights to both technical and non technical audiences
Strong ownership mindset and accountability for deliverables end to end
Demonstrated ability to influence stakeholders and recommend data driven solutions
Collaborative team player who can also work independently with minimal oversight
Mentorship mindset—able to guide junior analysts and review analytical work
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.
University / college degree, with 3+ years of relevant / direct industry experience.
In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.
Bachelor's degree

Nice To Haves

Analytical Thinking
Competitive Advantages
Data Analytics
Data Mining
Data Science
Informatics
Machine Learning (ML)
PL/SQL (Programming Language)
Certifications are often desired.

Responsibilities

Writing and optimizing code for data pipelines to ensure systems are highly efficient, scalable, and capable of handling large-scale financial datasets.
Collaborate with Finance Product owners, analysts to gather requirements and implement data solutions that meet business needs.
Analyzes and evaluates requirements by working with users, product owners and management and provides recommendations on the scope and complexity of the solution.
Build and optimize data architectures ensuring high performance, reliability, and security.
Proposes & designs data solutions to address complex business needs.
Prepares technical and procedural documentation required.
Acts as a lead by developing and documenting technical specifications for proposed solutions. This includes hands-on coding and testing as well to support solutions.
Participates in code reviews & overall testing.
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 applications to ensure its scalability, availability and maintainability.
Implements data migration and transformation activities/processes to ensure the accuracy and security of data solutions.