Data Engineer

About the role

Who We Are:

Headquartered in New York City, Take-Two Interactive Software, Inc. is a leading developer, publisher, and marketer of interactive entertainment for consumers around the globe. We develop and publish products principally through Rockstar Games, 2K, and Zynga. Our strategy is to create hit entertainment experiences, delivered on every platform relevant to our audience through a variety of sound business models. Our pillars - creativity, innovation, and efficiency - guide us as we strive to create the highest quality, most captivating experiences for our consumers. The Company’s common stock is publicly traded on NASDAQ under the symbol TTWO. For more corporate and product information please visit our website at http://www.take2games.com.

The Challenge

The Marketing Technology team works alongside the Labels (2K, Zynga, Rockstar Games, Social Point) Marketing, Community, and PR teams, managing and supporting the underlying technology stack used for Paid, Owned, and Earned marketing activity.

As a Data Engineer, you'll be a hands-on member of our MarTech team — building and maintaining the data pipelines and tooling that power marketing analytics and targeting. You'll work within established architectural patterns, contribute to design discussions, and grow your skills in distributed data processing in a creative and fast-moving environment.

You will build and maintain reliable, scalable data pipelines and contribute to the data systems that support marketing across our Labels. Working under the technical direction of senior engineers, you'll turn requirements into well-tested, production-ready data solutions and steadily take on greater ownership.

What You’ll Take On

- Build and maintain stable, scalable data pipelines that cleanse, structure, and integrate data sets into an accessible format for end-user analysis and targeting, across both stream and batch workflows.

- Contribute to improvements in data quality, monitoring, and availability, and help onboard new data sources in collaboration with the team.

- Implement data quality checks and tests within the team's data quality framework.

- Maintain accurate entries in the enterprise-wide data dictionary for the datasets and pipelines you own.

- Implement monitoring and alerting for the data solutions you build, following team standards.

- Test and monitor data for anomalies, troubleshoot issues, and resolve or escalate them appropriately.

- Participate in code reviews and follow established coding standards and source-management practices.

What You Bring

- 2+ years of working proficiency with SQL.

- Working proficiency with Python; exposure to PySpark on Databricks (or a strong willingness and aptitude to ramp up quickly).

- Familiarity with CI/CD concepts and tooling.

- Some experience working with large data sets and distributed processing (Spark / Hive / Hadoop), or solid understanding of the underlying concepts.