Senior Data Engineer at Epic Games
Cary, North Carolina, USA -
Full Time


Start Date

Immediate

Expiry Date

08 Sep, 25

Salary

0.0

Posted On

09 Jun, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

WHAT WE DO

Our mission is to provide a world-class platform that empowers the business to leverage data that will enhance, monitor, and support our products. We are responsible for data ingestion systems, processing pipelines, and various data stores all operating in the cloud. We operate at a petabyte scale, and support near real-time use cases as well as more traditional batch approaches.

ABOUT US

Epic Games spans across 25 countries with 46 studios and 4,500+ employees globally. For over 25 years, we’ve been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic’s award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent.

Responsibilities

WHAT YOU’LL DO

You will be responsible for designing, building, and maintaining our Metrics Catalog to ensure the reliability and efficiency of our data and systems used by our Experimentation tooling. Your role will include creating and maintaining data pipelines that transform and load data from various products in a way which is aligned with established data governance and stewardship practices. Additionally, you will collaborate with engineers, product managers, and data scientists to support Epic’s goals.

IN THIS ROLE, YOU WILL

  • Interact with product teams to understand how our different product areas track performance and measure success
  • Design and implement automated end-to-end ETL processes, including designing metrics and data anonymization, to prepare data for experimentation and monitoring purposes
  • Devise database structure for storing and efficiently accessing large data sets
  • Write well-tested SQL and Python modules
  • Collaborate with domain experts to build out a catalog of company core product metrics leveraged for AB testing
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