Staff Software Engineer – Data

OpenKrill; United States; Hybrid; USD 180,000 - 260,000; Full time

Job summary

Sony Interactive Entertainment is seeking a Staff Software Engineer – Data to lead the Real-Time Analytics Platform (RTAP). You will design, build, and operate high-throughput data systems, mentor engineers, and drive architectural choices across PlayStation data platforms.

You will partner with Data Engineering, Infrastructure, and Product teams to deliver scalable, reliable analytics capabilities and AI-powered automation for engineering workflows.

Qualifications

• Bachelor’s degree or equivalent practical experience in CS/engineering.
• 8+ years designing and building large-scale distributed systems with real-time data processing.
• Proficiency in Python; Scala is a plus for supporting platform components.

Responsibilities

• Design, build, and operate large-scale distributed data systems powering real-time analytics.
• Lead architecture and evolution of RTAP’s streaming and analytics platforms for scalability and reliability.
• Own platform capabilities end-to-end from design to production operations and performance tuning.
• Mentor engineers, review designs, and raise technical standards across teams.
• Partner with Product, Infrastructure, Security, and Platform teams to set technical strategy.

Skills

Python

Distributed systems

Real-time analytics

Leadership

System design

Mentoring engineers

Architectural decisions

Education

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

Tools

Apache Flink

Spark Structured Streaming

ClickHouse

Apache Druid

AWS MSK / Kafka

Databricks

Apache Iceberg

Job description

Why Sony Interactive Entertainment?

Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.

Staff Software Engineer – Data

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.

We’re looking for someone who is passionate about distributed systems, real-time analytics, and building scalable data platforms. You will work closely with Engineering, Product, Infrastructure, Security, and Data Engineering teams to shape technical strategy, influence architecture across organizations, mentor engineers, and help drive the long-term evolution of PlayStation’s data platform.

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.

Requirements

• 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.

In 90 days, you will have a detailed understanding of the Real-Time Analytics Platform and its role within PlayStation’s broader data ecosystem. You will be comfortable owning complex distributed systems initiatives, partnering closely with Product and Engineering teams, and driving large‑scale solutions from architecture through production delivery.

At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.

Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job‑related factors wh