Senior Data Engineer, PlayStation

• Typically 6+ years of professional data engineering or software engineering experience, including ownership of complex production data solutions
• Strong hands-on SQL and Python skills, with experience in distributed data processing using PySpark and/or Databricks
• Experience designing data pipelines and transformations using modern ETL/ELT tools and frameworks, such as dbt, Ab Initio or equivalent technologies
• Solid experience with cloud data platforms and warehouses, particularly Snowflake; knowledge of data modelling, dimensional design and data product principles
• Experience with orchestration, Git-based workflows, automated testing, CI/CD, monitoring and troubleshooting production data services
• Understanding of data security, access management, data quality, governance and regulatory considerations in enterprise environments
• Ability to influence technical decisions, mentor peers and communicate effectively with engineering and non-technical stakeholders
• Bachelor’s degree in a relevant discipline or equivalent practical experience

Desirable

• Design, build, test and maintain robust batch and near-real-time data pipelines and ETL/ELT workflows across enterprise systems, APIs, SaaS platforms and cloud data environments
• Develop reusable, well-documented data models and domain-aligned data products, translating complex business logic into reliable engineering solutions
• Lead technical design for assigned initiatives, evaluate trade-offs, and ensure solutions are scalable, secure, maintainable and cost-effective.
• Own solutions throughout the engineering lifecycle, from requirements and design through deployment, monitoring, incident resolution and continuous improvement
• Implement automated testing, data validation, reconciliation, lineage, observability, alerting and operational runbooks
• Apply engineering practices including version control, code review, CI/CD, infrastructure automation and appropriate change controls; improve performance and platform efficiency.
• Mentor engineers, lead technical reviews and contribute to shared patterns, coding standards and communities of practice
• Partner with business stakeholders, architects, security, governance, analytics and platform teams to clarify requirements, dependencies and data ownership
• Proactively identify delivery risks, technical debt and cross-team dependencies; communicate progress, options and recommendations clearly
• Enable trusted data for analytics, planning, automation and AI use cases while respecting privacy, security and access controls