Data Engineer III — Pipelines, Quality & Cloud

Comcast; Chicago (IL); On-site; USD 104,000 - 155,000; Full time

Benefits offered by this job

Bonus eligibility

Commission potential

Comprehensive benefits

Job summary

FreeWheel, a Comcast company, is seeking a data engineer to design and manage advanced data structures and pipelines that ensure data quality and accessibility across platforms. The role supports critical business initiatives with robust data solutions and governance.

The ideal candidate will have strong SQL, Python, and Spark experience, plus familiarity with cloud data warehouses and modern data stack components.

Qualifications

• Strong SQL proficiency and Python programming required.
• Experience with distributed computing frameworks (e.g., Apache Spark).
• Familiarity with cloud data warehouse management and data observability.

Responsibilities

• Designing and constructing data architectures and pipelines to standardize, transform, and ensure the integrity of data for business insights.
• Guaranteeing data quality throughout ingestion, processing, and loading phases with high standards.
• Engineering robust ingestion frameworks for various data types and monitoring data quality.
• Developing accessible data consumption methods via APIs, views, and extracts for applications.
• Implementing data solutions on Kubernetes, Teradata, and cloud services like AWS and Databricks.
• Collaborating with cross-functional teams to refine data sourcing and processing.

Skills

Data Lake

Data Lakehouse Architecture

Data Structures

Data Warehousing

Python

SQL

Education

Bachelor's Degree

Tools

Kubernetes

Teradata

AWS

Databricks

Looker

Job description

FreeWheel, a Comcast company, is seeking a data engineer to design and manage advanced data structures and pipelines that ensure data quality and accessibility across platforms. The role supports critical business initiatives with robust data solutions and governance.

The ideal candidate will have strong SQL, Python, and Spark experience, plus familiarity with cloud data warehouses and modern data stack components.