Staff Software Engineer, Data Governance & Trust

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 Governance & Trust

San Mateo, CA

About the role

Sony Interactive Entertainment is seeking a Staff Software Engineer to help shape and deliver the technical foundation for Data Governance and Trust across our data and AI ecosystem.

Our ambition is to make data understandable, reliable, reusable, and appropriately governed for the people, applications, and AI systems that depend on it. Achieving this requires shared platform capabilities, clear ownership, and governance practices embedded into how teams build and operate data products.

In this role, you will establish technical direction, lead initiatives across teams, and remain hands-on in architecture and implementation. You will connect metadata, lineage, data quality, semantic context, and policy controls into practical capabilities that help teams use data with confidence.

You will also be a trusted technical representative for the Data Governance and Trust group. We are looking for someone who can lead productive discussions, explain complex tradeoffs, navigate difficult conversations, and build alignment across engineering, business, governance, security, and privacy stakeholders.

This is an individual contributor leadership role with impact across teams.

What you will do

Set technical direction and deliver shared capabilities

• Shape the architecture and technical roadmap for Data Governance and Trust in partnership with engineering leadership, product partners, domain teams, and governance stakeholders.

• Lead initiatives from discovery and ambiguous requirements through design, implementation, adoption, and ongoing operation.

• Design and build services, integrations, APIs, and automation that connect metadata, ownership, classification, lineage, quality signals, and policy information across the data ecosystem.

• Establish reusable engineering patterns that embed trust requirements into data publishing, discovery, access, consumption, change, and retirement.

• Stay hands-on through prototypes, production code, design reviews, and the resolution of complex technical problems.

Lead conversations and build alignment

• Serve as a technical spokesperson for the group in architecture discussions, planning forums, domain engagements, and leadership reviews.

• Facilitate discussions among stakeholders with different priorities, surface disagreements constructively, and guide decisions toward clear outcomes.

• Explain technical choices, business implications, risks, and costs to both engineering and nontechnical audiences.

• Challenge assumptions respectfully, incorporate feedback, and help teams reach workable agreements on standards, ownership, and implementation.

• Document decisions, clarify responsibilities and dependencies, and follow through on commitments across teams.

• Build relationships that enable adoption through credibility, collaboration, and influence.

Make governance practical and sustainable

• Partner with governance, security, privacy, and domain stakeholders to translate agreed requirements into implementable controls and traceable evidence.

• Help domain teams define data contracts, quality expectations, ownership responsibilities, and lifecycle practices supported by shared platform capabilities.

• Connect quality and reliability signals to accountable owners, consumer communications, and remediation workflows.

• Evaluate build, buy, and integration choices based on interoperability, usability, reliability, operating cost, and long-term flexibility.

• Measure success through improvements in approved data use, adoption, reliability, reuse, and operational effort.

Prepare the foundation for AI consumption

• Develop ways to make business meaning, provenance, quality status, and permitted-use information available to applications and AI through supported interfaces.

• Partner with AI and platform teams on governed access to data and context, including traceability and defined behavior when required trust information is missing.

• Support shared semantic definitions and metadata models while preserving clear accountability within business domains.

Strengthen the team

• Mentor engineers in system design, technical judgment, stakeholder engagement, and leadership.

• Raise engineering standards for reliability, maintainability, testing, observability, and documentation.

• Help engineers take broader ownership and communicate their recommendations effectively.

What you bring

• A track record of designing, building, and operating production software or data platforms, with demonstrated impact across multiple teams.

• Deep knowledge of metadata management, data governance, lineage, data quality, privacy engineering, access controls, or closely related platform domains, grounded in practical delivery.

• Hands-on expertise building or extending metadata and catalog platforms such as Atlan, Alation, DataHub, OpenMetadata, or comparable systems.

• A practical understanding of federated ownership models, data stewardship, semantic models, business glossaries, or certified metrics.

• The ability to work across warehouse, lakehouse, streaming, and data transformation environments.

• Demonstrated delivery of data contracts, automated lineage, quality checks, or policy as code.

• Sound judgment in translating ambiguous business or policy requirements into clear technical designs and delivered outcomes.

• Proven ability to lead initiatives across teams without direct reporting authority.

• Skill in leading difficult technical or organizational conversations, resolving competing priorities, and securing clear decisions and commitments.

• Strong written and verbal communication, including architecture proposals, decision documents, and presentations tailored to different audiences.

• A collaborative approach grounded in listening, respectful challenge, and shared accountability.

• A commitment to mentoring engineers, supported by examples of improving the effectiveness of the teams around you.

What would be valuable

• Strong software engineering skills, including proficiency in a language such as Python, Java, or Go, and practical SQL experience.

• Experience with distributed systems, APIs, integrations, and cloud data infrastructure, including sound judgment about reliability, consistency, security, and failure handling.

• Experience implementing controls that generate operational evidence.

• Delivering governed data or context services for analytics, applications, machine learning, or AI agents.

• Leading platform adoption, modernization, or migration across organizational boundaries.

• Representing technical work through internal forums, technical writing, communities of practice, or external presentations.

What success looks like

• Partner teams understand the technical direction, the decisions required, and their responsibilities.

• Cross-team discussions produce documented decisions, accountable owners, and sustained follow-through.

• Priority workflows demonstrate connected governance capabilities in production, supported by clear operating ownership.

• Producers and consumers can access relevant meaning, ownership, lineage, quality, and permitted-use information within their workflows.

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