Senior Software Engineer, Data Engineering

Rockstar Games•New York, NY

2d•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 Games is seeking a Senior Software Engineer in Data Engineering to join a team focused on building a cutting-edge game analytics platform and tools to better understand our players and enhance their experience in our games. The ideal candidate will be skilled in developing complex ingestion and transformation processes with an emphasis on reliability and performance. In collaboration with Data Engineers, Machine Learning Engineers, and other Software Engineers, the candidate will empower the team of Analysts and Data Scientists to deliver data driven insights and applications to company stakeholders. This is a full-time, in-office position based out of Rockstar’s NYC headquarters in Downtown Manhattan. WHAT WE DO The Rockstar Games Online Services team builds the technology foundation that powers our games and delivers world-class player experiences. Our Data Engineering group manages petabyte-scale data, integrating dozens of streaming and batch sources with strict requirements for reliability, compliance, and low-latency processing. We approach data engineering with the rigor of software engineering by applying modern practices such as clean architecture, modular design, and automated testing. Our focus is on building scalable, reusable platforms and frameworks that enable our partners in Data Science and Game Development to deliver insights and unlock new possibilities for players.

Requirements

5+ years of professional experience building production software systems, preferably in a distributed or data-intensive environment.
Strong experience with Java (and/or Scala) as well as Python, in backend or data processing applications.
Experience designing and operating streaming systems using Kafka or Kafka Streams (or similar).
Experience working with event-driven architectures, including schema evolution and compatibility.
Experience building real-time and/or near-real-time data pipelines at scale.
Solid understanding of distributed systems concepts (partitioning, fault tolerance, backpressure, exactly-once/at-least-once semantics).
Familiarity with Avro, Protobuf, or similar serialization formats and schema governance practices.

Nice To Haves

Experience with Databricks, particularly for ingestion, bronze-layer processing, or structured streaming.
Experience deploying and scaling applications in containerized environments (e.g., Kubernetes, AKS).
Experience working with artifact repositories (e.g., Artifactory, ProGet, Maven repositories).
Experience with Infrastructure-as-Code (e.g., Terraform, Databricks Asset Bundles).
Familiarity with the Microsoft Azure cloud ecosystem.
Familiarity with Apache Spark.
Familiarity with CI/CD pipelines, automated testing, and deployment workflows.

Responsibilities

Design, build, and maintain high-throughput streaming and batch data processing services, with a primary focus on raw and bronze-level ingestion.
Develop and operate stream–based applications responsible for real-time data transformation, enrichment, validation, and routing.
Own and evolve event schemas and data contracts, including Avro schemas and Schema Registry governance.
Ensure scalability, fault tolerance, and performance of streaming and ingestion pipelines under heavy load.
Contribute to platform-level concerns such as deployment automation, observability, operational tooling, and CI/CD.
Participate in the design and implementation of cloud-native data infrastructure supporting real-time and batch workloads.

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