Sr. Data Engineer- Chicago, IL or Denver, CO- ONSITE 4 X Week

Comcast•Englewood, CO

63d•$118,139 - $177,209•Onsite

About The Position

FreeWheel, a Comcast company, provides comprehensive ad platforms for publishers, advertisers, and media buyers. Powered by premium video content, robust data, and advanced technology, we're making it easier for buyers and sellers to transact across all screens, data types, and sales channels. As a global company, we have offices in nine countries and can insert advertisements around the world. Job Summary We are seeking a highly skilled Data Engineer with expertise in SQL and either Python or Scala, experienced in building large-scale data pipelines using Apache Spark and designing robust data architectures on AWS. The ideal candidate will have hands-on experience in data lake architectures, open table formats (Delta Lake/Iceberg), and modern data platforms delivery self-service analytics for large number of users. If you are a problem solver, a data platform enthusiast, and someone who thrives in fast-paced environments, we'd love to hear from you!

Requirements

At-least 4+ years of experience in Data Engineering.
Proficient in at-least one of languages such as Python, Scala or Java or GoLang
Ability to craft SQLs for complex Lakehouse or warehouses
Hands-on experience in Spark and/or Snowflake is preferred
Firm grasp on concepts such as Lakehouse (like Apache Iceberg) and Warehouse
Firm grasp on Data Warehouse modeling paradigms
Firm understanding of Cloud based architectures
Problem solving skills

Nice To Haves

Experience in Looker or similar BI Modeling tool
Understanding of Semantic Layer such as Looker (Look ML), Snowflake or Databricks

Responsibilities

Architect, design, and develop high-performance, scalable data pipelines.
Develop large scale and complex Big Data ETL using modern frameworks such as DBT and Databricks Delta Live Tables (DLT)
Define and implement data lake architectures and open table formats (e.g., Delta Lake, Iceberg).
Establish and enforce best practices for data engineering, ensuring data quality, integrity, and performance.
Drive observability and monitoring for data pipelines, implementing data catalogs and lineage tracking.
Ability to own critical modules for complex and large-scale Batch ETL models and ability to articulate models to Product, Engineering and Leadership
Effectively context switch between multiple priorities, balancing long-term architectural goals with immediate business needs.
Develop complex Semantic layers and help create customer facing self-service analytics
Consistent exercise of independent judgment and discretion in matters of significance.
Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary.
Other duties and responsibilities as assigned.