Senior Data Engineer

Rockstar Games•New York, NY

18d•Onsite

About The Position

At Rockstar Games, we create world-class entertainment experiences. Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. Rockstar is seeking a Senior Data Engineer to join a team building a cutting-edge game analytics platform and tools to better understand our players and enhance their experience across our titles. The ideal candidate will be skilled in developing complex ingestions and transformation processes with an emphasis on reliability and performance. In collaboration with other Data Engineers, Machine Learning Engineers, and Software Engineers, the candidate will empower the team of Analysts and Data Scientists to deliver data driven insights and applications across the company. This is a full-time, in-office position based out of Rockstar’s NYC headquarters in Downtown Manhattan. WHAT WE DO The Rockstar Data Engineering team provides insights and actionable results to a wide variety of teams across the organization in support of their decision making. We work with petabyte-scale data in Azure and Databricks, building both real-time and batch pipelines that power analytics, machine learning, and player experience improvements.

Requirements

5+ years of work experience with designing and development of modern data pipelines.
4+ years of experience with Python for data engineering (building maintainable, testable code) and Spark for large-scale data processing.
Strong software engineering fundamentals – design patterns, testing strategies (unit, integration) code review practices, system design thinking.
Expert-level SQL and deep understanding of query optimization, data structures, and performance tuning.
Track record of building and optimizing terabyte or petabyte-scale data warehouses.
Ability to work independently on loosely-defined projects – gathering requirements, making architectural decisions, and following through completion.
Experience building Real-Time and/or Near-Real-Time data pipelines.
Outstanding communication and interpersonal skills, including the ability to tailor communication style to technical and non-technical audiences.

Nice To Haves

Databricks platform experience (Delta Lake, Unity Catalog, Workflows).
Experience with Data warehouses (such as data modeling and technical architectures) and infrastructure components.
Containerization and orchestration (Docker, Kubernetes).
Experience with Java or Scala.
Experience with CI/CD (TeamCity, Octopus).
RESTful API design, usage, and consumption.
Gaming industry experience or passion for games.
Experience in Machine Learning pipelines and popular libraries.

Responsibilities

Design, build, and own real-time and batch data pipelines in Azure Databricks using Spark, Airflow, and modern orchestration and build tools.
Drive engineering excellence by implementing robust testing practices (unit, integration), code review standards, and CI/CD automation.
Architect Data Models for massive-scale MPP engines (Databricks/Spark, SQL, Snowflake) that balance performance, maintainability, and analytical flexibility.
Collaborate with Data Scientists, Analysts, and ML Engineers to gather requirements, understand use cases, and deliver reliable data products.
Identify and implement improvements to our data platform, pipelines, and development processes with autonomy to POC new approaches and technologies.
Mentor, elevate, and learn with the team by sharing insights, maintaining documentation, and establishing engineering best practices.
Own projects end-to-end, from gathering requirements and technical design through implementation, testing, and production support.

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