Staff Software Engineer - Data

Responsibilities

• 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.