Data Engineer , Comcast Global Audit

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.

The Data Engineer (Level
3) plays an important role in driving best practices supporting Comcast Global Audit (CGA) by sustaining a modern audit data platform supporting advanced data analytics, automation, and artificial intelligence. This role focuses on maintaining a scalable, resilient data platform architecture and related data pipelines with a strong emphasis on automation, quality, governance, and observability. The ideal candidate brings technical expertise, system thinking, and the ability to lead technical decisions that drive scalability, trust, and transparency across the audit data ecosystem.

• Maintaining the data platform architecture and environments, including patching, monitoring, tuning, and other operational tasks.
• Reviewing and supporting data pipelines and queries running through the data platform, providing feedback regarding performance tuning and scalable query best practices.
• Upgrading and maintaining systems and tools used by the audit team, such as Team Mate+.

This role offers broad exposure to the Comcast Corporation through the audit process and provides opportunities to influence risk management strategies through data‑driven insights.

• Demonstrates project management skills for data platform maintenance / upgrades, including proposing project plans, scheduling deliverables across CGA teams, executing per plan, and messaging status/issues to management.
• Designs, builds, and maintains resilient, automated data pipelines.
• Introduces and maintains data quality checks and observability tooling (e.g., Monte Carlo, Great Expectations) to ensure data accuracy, lineage, and pipeline reliability.
• Builds end‑to‑end pipeline monitoring: logging, alerting, and traceability from source ingestion to report‑ready datasets.
• Supports CI/CD pipelines (e.g., Git Hub Actions) for secure, auditable deployments of infrastructure and code.
• Manages data integration across diverse sources (APIs, SFTP, databases) using secure, repeatable patterns with version control and infrastructure‑as‑code practices.
• Independently delivers robust data engineering solutions with minimal supervision, including root‑cause analysis and long‑term fixes.
• Leads code reviews and contributes to evolving team‑wide engineering standards, documentation, and architecture, championing best practices.
• Maintains strong operational rigor in maintaining cyber compliance, patching, resiliency, upgrades, etc.
• Ensures all data is secure and follows company policies regarding data classification.
• Analyzes data to assess compliance with established policies/procedures, best practices, US GAAP, and legal/governmental requirements.
• Uses data concepts, tools, and programming techniques including SQL, dbt, Snowflake, Airflow, Tableau, AWS, MS SQL Server, Oracle BI, Teradata, Databricks, Alteryx, Spark, Python, and R to perform ETL and data analysis activities.
• Develops process flows, prototypes, and requirements documentation to accelerate stakeholder understanding and guide solution development.
• Creates, documents, and executes support process steps and test procedures to ensure data deliverables are accurate and sustainable.
• Facilitates discussions that lead to decision‑making throughout the lifecycle of creating and enhancing data solutions.
• Prepares clear and well‑organized analysis work papers, documenting root‑cause (as applicable), work performed, findings, and recommendations.
• Creates graphical…