Data Platform Engineer

About the role

2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K's portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today's most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment. Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K's portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K, renowned BioShock®️, Borderlands®️, Mafia, Sid Meier's Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don't meet every requirement for the role. If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply! What We Need The Data Platform Engineer is responsible for designing and evolving the core architectural foundation of 2K's data ecosystem. While Data Engineers build pipelines and DataOps Engineers manage reliability, the Data Platform Engineer focuses on building the underlying platforms-including Snowflake, Databricks, Kafka, and internal frameworks-that enable self-service data capabilities across the organization. At the P4 level, this role ensures high-performance environment scalability for billions of global player events and creates seamless interoperability between complex data systems.

Responsibilities

• Platform Architecture & Development: Lead the design, implementation, and optimization of core data platform components, including Snowflake, Databricks, and AWS S3 Data Lakes.
• Streaming Infrastructure: Manage and scale high-throughput streaming systems using Kafka or Kinesis to support real-time game telemetry and low-latency analytics.
• Self-Service Enablement: Develop "Data-as-a-Service" (DaaS) features that allow Business Units and Studios to onboard data and manage access with minimal friction.
• Distributed Systems Optimization: Optimize Spark and PySpark applications for performance and cost-efficiency across large-scale distributed clusters.
• Security & RBAC Architecture: Design and automate granular access control models to ensure data security and compliance with global regulations (e.g., GDPR, CCPA).
• Interoperability & Standards: Ensure seamless data flow and interoperability between disparate platforms (utilizing technologies like Apache Iceberg) to maintain a Single Source of Truth (SSOT).
• Technical Leadership: Serve as a subject matter expert for the data platform, translating complex business needs into scalable technical requirements and platform features.
• Who We Think Will Be A Great Fit
• Architectural Depth: Demonstrates a deep understanding of how platform components interact and scale within a global data ecosystem.
• Innovation & Efficiency: Drives the adoption of new technologies and methodologies to improve platform performance and reduce operational overhead.
• Problem Solving: Resolves complex, high-impact technical issues related to distributed systems and data availability.
• Collaboration: Partners effectively with Data Scientists, Data Engineers, and Studio Leads to provide a high-quality developer experience.
• Strategic Thinking: Anticipates future platform needs and aligns architectural decisions with long-term business goals.
• Required Qualifications, Knowledge, and Job-Related Skills
• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• Experience: 6+ years of professional experience in data platform or distributed systems engineering in high-volume environments.
• Core Technical Stack: Mastery of SQL and Python; expert knowledge of big data processing frameworks like Spark.
• Cloud Ecosystem: Deep proficiency in AWS services (S3, EKS, IAM, SNS/SQS) and extensive experience with Snowflake or Databricks.
• Orchestration: Experience building or extending workflow orchestration platforms like Apache Airflow.
• Architecture Mindset: Strong understanding of data modeling methodologies (Kimball, Inmon, Data Vault) and how they apply to modern

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