Engineer 3, Data Engineering

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast.

This job independently designs, develops, and manages advanced data structures and pipelines, ensuring data quality and accessibility. It strategically implements data solutions across various platforms, maintaining compliance with privacy and regulatory standards. The role acts as a technical resource, optimizing data processes and storage to support key business initiatives.

Data Engineer 3 – Data Governance Position Summary: We are seeking a Data Governance Engineer 3 with strong Data Engineering expertise and practical experience implementing Data Governance, Data Quality, Metadata Management, and Lineage solutions. The ideal candidate will play a key role in enabling trusted, governed, and high-quality enterprise data while building scalable cloud-based data platforms.

Design, develop, and optimize enterprise-scale data pipelines and ETL/ELT frameworks using Python, PySpark, and Apache Spark. Build and support scalable data platforms on AWS using services such as S3, Glue, Athena, Redshift, and Lambda. Lead development of robust data ingestion, transformation, and integration solutions for large-scale datasets. Design and implement data quality frameworks, validation controls, monitoring mechanisms, and remediation processes. Drive metadata management, data cataloging, data lineage, and business glossary initiatives across data platforms. Collaborate with Data Stewards, Data Owners, Architects, Product Teams, and Engineering teams to implement governance requirements. Define and promote data governance standards, controls, and best practices across data engineering teams. Support governance adoption through automation, engineering standards, and reusable framework development. Develop and maintain data models supporting reporting, analytics, and business intelligence requirements. Build solutions based on Medallion Architecture and Lakehouse design principles. Contribute to Common Data Engineering frameworks, standards, accelerators, and reusable components. Analyze and resolve complex data quality, reliability, and performance issues across data platforms. Ensure compliance with enterprise security, privacy, regulatory, and governance requirements. Review code, mentor junior engineers, and contribute to the overall technical growth of the team. Drive operational excellence through monitoring, optimization, automation, and continuous improvement initiatives.

4.5 - 7.5 years of experience in Data Engineering, Data Platform Engineering, or related fields. Strong hands-on expertise in Python. Advanced experience with PySpark or Apache Spark. Strong SQL development, optimization, and data modeling skills. Experience working with AWS-based data platforms and services. Hands-on experience designing and maintaining ETL solutions. Understanding modern Data Architecture, Data Warehousing, and Lakehouse concepts. Experience with Git, CI/CD pipelines, and Agile delivery models. Practical experience in Data Governance implementation. Knowledge of Metadata Management, Data Cataloging, Data Lineage, and Data Stewardship. Exposure to MDM, data compliance, and regulatory requirements. Good to Have Experience implementing Data Quality frameworks and controls. Experience with governance