Senior Technical Program Manager, PlayStation

• This is a senior individual contributor role suited to someone who is highly organised, data-driven, and comfortable working with technical stakeholders across a varied data ecosystem
• Significant experience (typically 7+ years) in technical program management or project management in a software, data, or cloud engineering context
• Proven track record of driving cross-team programs from planning through delivery, with demonstrable impact on reliability, performance, or efficiency
• Experience working closely with operations, SRE, or platform teams on production services
• Strong skills in planning, dependency management, and risk management across multiple teams
• Comfortable operating in an agile environment, coordinating between different teams and methodologies
• Able to break down ambiguous objectives into clear, sequenced workstreams
• Excellent written and verbal communication; able to tailor information for engineers, managers, and senior leaders
• Effective at influencing without authority, building trust with engineering managers and cross-functional partners
• Comfortable facilitating workshops, retrospectives, and decision-making forums
• Proficient with tools such as JIRA, Confluence, and similar project tracking and documentation systems
• Working familiarity (conceptual and conversational) with AWS cloud services, Snowflake or similar cloud data warehouses, Kubernetes, and ETL/ELT data pipelines

Desirable

• The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation
• The Senior Technical Program Manager for Data Platforms & Operations will drive the planning, coordination, and delivery of complex initiatives across our cloud-based data platforms and their operations
• In this role the successful candidate will work closely with engineering managers, SRE/operations teams, and data/AI engineering teams who own the data products and data services which rely on the efficient running and delivery of data platforms
• Coordinate cross-team work so platform and operational changes land predictably and safely
• Structure delivery (roadmaps, plans, dependencies, risks) for data platform programs
• Improve operational performance by assisting engineering managers, ensuring metrics and runbooks are part of the delivery process
• Provide transparency to leadership via clear, metric-led reporting on status, risk, and outcomes
• Plan and run cross-platform programs for data platform and operational initiatives (e.g. major upgrades, reliability improvements, cost optimisation, new platform capabilities)
• Build and maintain integrated program plans (scope, milestones, dependencies, risks, decision points) across multiple engineering and operations teams
• Facilitate regular delivery cadences (stand-ups, status reviews) with engineering managers and leads; ensure actions are owned and tracked to completion
• Ensure that program objectives are clearly defined, measurable, and aligned with business outcomes, such as:
• Improved platform availability and reliability
• Reduced incident frequency and MTTR targets
• Improved data freshness, latency, and throughput for key workloads
• Partner with engineering managers, SREs, and operations teams to assist them in coordinating operational activities are delivered by data platform teams:
• Change calendars, release planning, and operational readiness reviews
• Operational playbooks and runbook readiness for new features or platform changes
• Coordinated communication during planned maintenance and impactful changes
• Align with service owners (engineering managers) on operational priorities and schedules, helping sequence work in a way that balances reliability, feature delivery, and cost
• Work with engineering managers and service owners to ensure platform and operational KPIs, are part of the end delivery:
• SLA/SLO/SLI for data platforms and pipelines (e.g. uptime, data freshness, query performance)
• Operational metrics such as incident rate, MTTR, change success rate, and capacity utilisation
• Ensure consistent measurement and reporting of delivery metrics across programs and operational areas:
• Curate and maintain dashboards and status reports for leadership
• Highlight trends, risks, and trade-offs in a clear and concise way
• Use analytics to prioritise improvements, identify systemic issues, and quantify impact of program work
• Facilitate coordination across:
• Data platform engineering (cloud infrastructure, Kubernetes, data platform services)
• Data engineering and ETL/ELT teams
• AI/ML engineering teams consuming data platform capabilities
• Operations, SRE, and service desk teams
• Align teams on priorities, sequencing, and dependencies for shared initiatives, ensuring upstream and downstream impacts are understood
• Communicate program status to stakeholders at multiple levels:
• Concise executive summaries of progress, risk, and impact
• Detailed views for engineering teams on dependencies, decisions, and next steps
• Support governance initiatives for data platforms are part of the delivery process:
• Align teams on documenting and delivering templates/checklists for change reviews, and operational readiness
• Promote continuous improvement initiatives focused on:
• Increasing automation in operations and delivery processes
• Reducing toil and manual coordination where possible
• Strengthening platform resilience and reducing operational risk
• Capture and socialise lessons learned across programs to improve future planning, estimation, and operational practices