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

PNC Bank•Pittsburgh, PA

1d•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 - ETL| Informatica | SQL PL/SQL | RDBMS | Data Warehousing within PNC's Technology organization, you will be based in Pittsburgh PA. 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.

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 )
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
Roles at this level typically require a 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.

Nice To Haves

Creative problem solver who can tackle complex data challenges.
Analytical Thinking
Competitive Advantages
Data Analytics
Data Mining
Data Science
Informatics
Machine Learning (ML)
PL/SQL (Programming Language)
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

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.
Mentor who can guide junior engineers and contributes to team growth.
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.