SUPER SENIOR DATA ENGINEER (1 POSITION) @ PNC
PNC is currently seeking a highly experienced Super Senior Data Engineer with over 10 years of professional experience to join their team in Pittsburgh, PA. The successful candidate will play a critical role in designing, building, and maintaining scalable data pipelines leveraging the full suite of AWS cloud services. This position involves developing and optimizing sophisticated ETL and ELT workflows to handle both structured and semi-structured data, ensuring that high-performance analytics are available for business decision-making. Working within an agile environment, the role demands a expert-level understanding of data processing jobs using Python and PySpark.
In addition to pipeline construction, the engineer will be responsible for integrating and managing data within the Snowflake cloud data warehouse. This includes writing complex SQL queries for data transformation and validation, as well as supporting Power BI dashboards by delivering curated, analytics-ready datasets. Candidates must demonstrate a strong commitment to data quality, governance, performance, and security best practices. This role is offered on a W2 basis and is ideal for individuals with prior experience in the financial services or banking domain who are looking to apply their technical leadership in a dynamic corporate environment.
In addition to pipeline construction, the engineer will be responsible for integrating and managing data within the Snowflake cloud data warehouse. This includes writing complex SQL queries for data transformation and validation, as well as supporting Power BI dashboards by delivering curated, analytics-ready datasets. Candidates must demonstrate a strong commitment to data quality, governance, performance, and security best practices. This role is offered on a W2 basis and is ideal for individuals with prior experience in the financial services or banking domain who are looking to apply their technical leadership in a dynamic corporate environment.
Key Requirements
Minimum of 10 years of professional experience in Data Engineering or a related field.
Advanced proficiency in SQL, including complex querying and performance tuning.
Extensive experience designing and maintaining scalable data pipelines on AWS.
Expert knowledge of Python and PySpark for large-scale data processing.
Hands-on experience with Snowflake cloud data warehouse management and integration.
Proven ability to develop and optimize ETL/ELT workflows for various data formats.
Experience supporting Power BI through data modeling and performance optimization.
Familiarity with AWS services such as S3, Glue, EMR, Lambda, and Redshift.
Strong understanding of data quality frameworks, governance, and security best practices.
Ability to work effectively in an Agile/Scrum environment with cross-functional teams.