Data Engineer

Overview

Why Play Station?

Play Station isn't just the Best Place to Play - it's also the Best Place to Work. Today, we're recognized as a global leader in entertainment producing The Play Station family of products and services including PlayStation5, PlayStation4, PlayStation

VR, Play Station Plus , acclaimed Play Station software titles from Play Station Studios, and more.

Play Station also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The Play Station brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.

ICDS Staff Data Engineer

Location:
San Mateo, CA

Play Station is for The Players.

With over 150 million customers in 109 countries, Sony Interactive Entertainment (SIE) is committed to using data to understand The Players: our customers, better than anyone else. Using the networked power of Play Station platforms, we learn how they use them for gaming, streaming services, payments, and how we can improve their customer experience. We work with game developers, marketing, R&D, Play Station Store , and many other parts of Sony to constantly improve our customer experience and maximize our business potential.

The ICDS DE team has grown rapidly and currently comprises approximately 170 staff across London and California, covering architecture and platform support, data processing, and technical program management.

ICDS delivers data that powers Analytics, Data sciences, Marketing, ML, and multiple other teams across the Play Station business: high quality, valuable to the user, accessible, and continuously improving.

Technical Leadership & Architecture

• Lead the design and evolution of large-scale batch and real-time data platforms using Apache Spark, Flink, and Databricks
• Define streaming and event-driven architectures (low-latency, exactly-once, high-throughput) using Flink and Scala
• Set architectural standards for data reliability, scalability, observability, and cost efficiency
• Own end-to-end system design for mission-critical data products
  , from ingestion to consumption

Data Pipeline Development

• Build and maintain high-performance data pipelines in Scala and Python for both batch and streaming workloads
• Develop real-time processing jobs (windowing, stateful processing, joins) using Flink
• Optimize Spark jobs for performance, cost, and data correctness on Databricks
• Implement robust data quality checks, schema evolution, and fault tolerance

Platform & Operations Excellence

• Drive best practices for CI/CD, automated testing, and deployment of data pipelines
• Establish monitoring, alerting, and SLAs for data systems
• Lead efforts in capacity planning, performance tuning, and cost optimization
• Partner with SRE / Platform teams on reliability, scaling, and incident response
• Ensure code is fully scalable, maintainable, and performant

Cross-Functional Collaboration

• Work closely with product managers, analytics, ML, and backend teams to translate business requirements into scalable data solutions
• Enable downstream use cases including analytics, reporting, experimentation, and machine learning
• Influence data modeling and contract design to ensure long-term platform sustainability
• Work proactively to address project requirements and communicate issues with lead time to address delivery risk
• Requires the ability to work in a global and multi-cultural environment with occasional travel

Mentorship & Influence

• Mentor senior and mid-level data engineers; raise the technical bar across the organization
• Lead technical reviews, design discussions, and post-incident analyses
• Influence data engineering strategy across multiple teams or domains
• Act as a go-to expert for streaming systems, Spark optimization, and distributed data processing

Governance, Security & Compliance

• Ensure data platforms adhere to security, privacy, and compliance requirements
• Define best practices for data access control, lineage, and auditing
• Drive standardization around data formats, schemas, and lifecycle management

Experience

• BS Degree in Engineering or Masters, Computer Science or equivalent experience
• 3-5+ years in a technical leadership or staff-level role (design ownership, mentoring, architecture decisions)
• 10-12+ years of hands-on experience building and operating large-scale data pipelines and platforms
• 10-12+ years of relevant industry experience, including ownership of complex, high-impact data systems used at scale
• 10
  - 12+ years of experience in database development, programming (Scala,Python) design, and analysis
• 10
  - 12+ years of experience with distributed framework like Spark, Flink
• 5-7+ years of experience with streaming services - Flink, Kafka
• 10
  - 12+ years of experience with data and ETL programming (Databricks, Ab Initio)
• 7
  - 10+ years of experience with AWS services (EKS, S3, EC2, Kinesis, Dynamo
  
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