[Hiring] Staff Software Engineer – Data @PlayStation Global

Role Description

Do you want to join a team of talented engineers building the next generation of real-time data platforms that power analytics and data-driven experiences across PlayStation? As part of our Data Platform team, you will play a key technical leadership role in designing and evolving the Real-Time Analytics Platform (RTAP), enabling high-throughput, low-latency analytics and stream processing at PlayStation scale.

The Software Engineers within our Platform Engineering Group design, build, document, and operate large-scale distributed data platforms that support real-time and near real-time analytics across PlayStation. You will solve complex distributed systems challenges, evolve our streaming and analytics architecture, integrate AI-powered platform capabilities, and improve scalability, reliability, performance, and developer productivity.

Responsibilities

• Design, build, and operate large-scale distributed data systems that power real-time and near real-time analytics, and data-driven applications across PlayStation.
• Lead the architecture and evolution of RTAP’s stream processing and analytics platforms, improving scalability, reliability, performance, and developer productivity.
• Own critical platform capabilities end-to-end from architecture and implementation through production operations, performance optimization, reliability, and lifecycle management.
• Build and optimize distributed data services using technologies such as Apache Flink, Spark Structured Streaming, ClickHouse, and Apache Druid to support high-throughput, low-latency workloads.
• Partner with Data Engineering teams to integrate batch and streaming workloads using modern lakehouse architectures and build interoperable, scalable data platforms.
• Build AI-powered capabilities to automate engineering workflows, improve data quality, simplify platform operations, accelerate troubleshooting, and enhance developer productivity.
• Establish technical standards and engineering best practices for distributed systems, stream processing, data modeling, query optimization and platform reliability.
• Mentor engineers across the organization by reviewing architecture, designs, and code while raising the technical bar through coaching and technical leadership.
• Partner with Product, Infrastructure, Security, and Platform Engineering teams to define long-term technical strategy and deliver scalable platform capabilities aligned with business priorities.
• Investigate and resolve complex production challenges involving high-throughput, low-latency distributed systems, ensuring high availability and operational excellence.
• Participate in the team's production support and on-call rotation, leading incident response, conducting root-cause analysis, and implementing reliability improvements that strengthen the platform over time.
• Evaluate emerging technologies and distributed data platforms, recommending investments that improve scalability, reliability, developer productivity, and cost efficiency.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• 8+ years of experience designing and building large-scale distributed systems, with expertise in real-time data processing, analytics, or data platform engineering.
• Strong proficiency in Python, with experience building production-grade distributed systems and data processing applications. Experience with Scala is beneficial for supporting and evolving existing platform components.
• Hands-on expertise designing and operating large-scale stream processing applications using Apache Flink, Apache Spark Structured Streaming, or equivalent distributed streaming technologies.
• Production experience designing, operating, and optimizing distributed analytics platforms using ClickHouse, Apache Druid, or equivalent high-performance OLAP/analytics databases, including query optimization, data modeling, and performance tuning at scale.
• Experience building and consuming event-driven data pipelines using AWS MSK, Apache Kafka, or equivalent messaging platforms, with a focus on developing reliable, scalable data processing applications.
• Experience applying AI/ML techniques and modern AI tooling to automate engineering workflows, improve data pipelines, simplify platform operations, and enhance developer productivity.
• Strong systems design skills with the ability to evaluate architectural trade-offs across scalability, latency, throughput, consistency, reliability, and cost.
• Demonstrated technical leadership through architecture ownership, mentoring engineers, and influencing technical decisions across multiple teams.

Nice to Have

• Experience with Databricks, Apache Iceberg, or modern lakehouse architectures, with the ability to design and integrate batch and streaming workloads into scalable, production-grade data platforms.
• Experience building or operating multi-tenant, self-service data platforms supporting multiple engineering organizations.
• Experience collaborating with globally distributed engineering teams across multiple organizations and time zones to deliver shared platform capabilities and drive technical alignment.

Your First 90 Days

• 30 Days: Develop a strong understanding of the platform’s architecture, capabilities, engineering practices, and roadmap. Begin contributing to architecture discussions, feature development, design reviews, and production support. Build relationships within the team as well as across the Data Platform organization.
• 60 Days: Take technical ownership of a major platform capability or architectural area. Identify opportunities to improve scalability, performance, reliability, or developer productivity. Collaborate with Data Engineering, Infrastructure, Product, and other partner teams on cross-platform initiatives.
• 90 Days: Lead the design and delivery of key roadmap initiatives for the team. Influence technical direction across teams and mentor engineers on distributed systems and platform engineering best practices. Establish clear architectural recommendations for the next phase of the platform’s evolution.

Benefits

• Medical, dental, vision coverage.
• Matching 401(k).
• Paid time off.
• Wellness program.
• Employee discounts for Sony products.
• Potential eligibility for a bonus package.

Equal Opportunity Statement

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.

We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.

Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.