Staff Data Platform Engineer – Real-Time Analytics

Sony Interactive Entertainment

San Diego (CA)

Hybrid

USD 198,000 - 297,000

Full time

4 days ago
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Benefits offered by this job

Employee discounts

Job summary

Sony Interactive Entertainment is seeking a Staff Software Engineer – Data to lead the Real-Time Analytics Platform (RTAP) at PlayStation scale. You will design and evolve distributed data systems, drive AI-powered platform capabilities, and mentor engineers across multiple teams in a hybrid work environment.

The role emphasizes ownership of architecture, reliability, and performance of real-time analytics, with collaboration across Data Engineering, Infrastructure, and Product teams.

Qualifications

  • Bachelor's degree in CS, Engineering, or related field.
  • 8+ years designing large-scale distributed systems.
  • Strong Python and optional Scala expertise.
  • Hands-on with Flink, Spark Streaming, Kafka.
  • Experience with ClickHouse or Druid for OLAP analytics.

Responsibilities

  • Design, build, and operate large-scale data platforms for real-time analytics.
  • Lead architecture and evolution of streaming/analytics platforms.
  • Own end-to-end platform capabilities from design to production.
  • Mentor engineers and raise technical standards across teams.
  • Collaborate with Product, Infrastructure, Security, and Platform teams.

Skills

Python
Scala
Distributed systems
Real-time analytics
Apache Flink
Apache Spark
Apache Kafka
ClickHouse
Apache Druid
AI/ML

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

AWS MSK

Job description

Sony Interactive Entertainment is seeking a Staff Software Engineer – Data to lead the Real-Time Analytics Platform (RTAP) at PlayStation scale. You will design and evolve distributed data systems, drive AI-powered platform capabilities, and mentor engineers across multiple teams in a hybrid work environment.

The role emphasizes ownership of architecture, reliability, and performance of real-time analytics, with collaboration across Data Engineering, Infrastructure, and Product teams.

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