Design, build, and operate large-scale distributed data systems for real-time and near-real-time analytics and data-driven applications.
Lead the architecture and evolution of stream-processing and analytics platforms, improving scalability, reliability, performance, and developer productivity.
Own critical platform capabilities end-to-end, including architecture, implementation, production operations, optimization, reliability, and lifecycle management.
Build and optimize distributed data services using Apache Flink, Spark Structured Streaming, ClickHouse, and Apache Druid.
Integrate batch and streaming workloads through modern lakehouse architectures in partnership with Data Engineering teams.
Build AI-powered capabilities that improve data quality, platform operations, troubleshooting, engineering workflows, and developer productivity.
Establish technical standards and best practices for distributed systems, stream processing, data modeling, query optimization, and platform reliability.
Mentor engineers through architecture, design, and code reviews and provide technical leadership across the organization.
Partner with Product, Infrastructure, Security, and Platform Engineering teams on technical strategy and scalable platform capabilities.
Investigate and resolve complex production issues, participate in on-call rotation, lead incident response, conduct root-cause analysis, and implement reliability improvements.
Evaluate emerging distributed data technologies and recommend investments related to scalability, reliability, productivity, and cost efficiency.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
At least 8 years of experience designing and building large-scale distributed systems, with expertise in real-time data processing, analytics, or data platform engineering.
Strong Python proficiency and experience building production-grade distributed systems and data-processing applications.
Experience with Scala is beneficial for supporting and evolving existing platform components.
Hands-on experience designing and operating stream-processing applications with Apache Flink, Apache Spark Structured Streaming, or equivalent technologies.
Production experience designing, operating, and optimizing distributed analytics platforms using ClickHouse, Apache Druid, or equivalent OLAP and analytics databases.
Experience with 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.
Experience applying AI/ML techniques and modern AI tooling to engineering workflows, data pipelines, platform operations, and developer productivity.
Strong systems design skills covering scalability, latency, throughput, consistency, reliability, and cost trade-offs.
Demonstrated technical leadership through architecture ownership, mentoring, and influencing technical decisions across multiple teams.
Experience with Databricks, Apache Iceberg, or modern lakehouse architectures is preferred.
Experience building or operating multi-tenant, self-service data platforms is preferred.
Experience collaborating with globally distributed engineering teams is preferred.
Benefits
Medical, dental, and vision benefits.
Matching 401(k).
Paid time off and wellness program.
Employee discounts on Sony products.
Potential eligibility for a bonus package.
Hybrid working policy; individual base pay may vary based on job-related factors and location.
Background checks are conducted at the offer stage.
Salary: $198k - $297k/yr
PlayStation Global
At PlayStation Global, we focus on creating user-friendly solutions that simplify processes, improve efficiency, and empower teams to succeed.