Senior Data Engineer

Description

The company behind the PlayStation brand is a subsidiary of Sony Group Corporation. It makes hardware and network services used by more than 100 million people and also owns well-known entertainment intellectual property.

The team is Player Data Engineering. It builds reusable pipelines, integration services and curated data products for Commerce, hardware, game play, products and services, and accounts.

This is a hands-on senior individual contributor role that works with engineering, platform, product and business teams. You take full ownership of complex solutions and raise engineering standards by leading technical work and mentoring others.

The goal is reliable, governed Player data that is ready for AI use.

Responsibilities

• Design, build, test and maintain batch and near-real-time pipelines and ETL/ELT workflows across Player data systems, APIs, Snowflake and cloud data environments.
• Create reusable, well-documented data models and domain data products, turning complex business logic into dependable engineering solutions.
• Lead technical design for assigned work, weigh trade-offs, and make sure solutions are scalable, secure, maintainable and cost-effective.
• Own solutions from requirements and design through deployment, monitoring, incident resolution and ongoing improvement.
• Build automated testing, data validation, reconciliation, lineage, observability, alerting and operational runbooks.
• Use version control, code review, CI/CD, infrastructure automation and change controls, and improve performance and platform efficiency.
• Mentor engineers, lead technical reviews and help shape shared patterns, coding standards and communities of practice.
• Work with TPMs, business stakeholders, architects, security, governance, analytics and platform teams to clarify requirements, dependencies and data ownership.
• Spot delivery risks, technical debt and cross-team dependencies early, and communicate progress, options and recommendations clearly.
• Make data trustworthy for analytics, planning, automation and AI, while respecting privacy, security and access controls.

Requirements

• Typically 5+ years of professional data or software engineering experience, including owning complex production data solutions.
• Experience building pipelines and transformations with modern ETL/ELT tools and frameworks such as dbt, Ab Initio or equivalents.
• Solid experience with cloud data platforms and warehouses, especially Snowflake, plus data modelling, dimensional design and data product principles.
• Experience with orchestration, Kubernetes, Git-based workflows, automated testing, CI/CD, and monitoring and troubleshooting production data services.
• Understanding of data security, access management, data quality, governance and regulatory requirements in enterprise settings.
• Experience using AI coding assistants, agentic workflows and AI-driven development tools to speed up engineering and improve code quality.
• Familiarity with building or integrating AI agents into data engineering workflows is a strong plus.
• Ability to influence technical decisions, mentor peers and communicate with both engineers and non-technical stakeholders.
• Bachelor's degree in a relevant discipline or equivalent practical experience.
• Desirable: strong hands-on SQL and Python skills, with experience in distributed processing using PySpark and/or Databricks.
• Desirable: experience with AWS services, APIs, event-driven integration and infrastructure as code.
• Desirable: exposure to AI/ML data preparation, data observability, metadata management and modern data governance.
• Desirable: experience working with globally distributed teams and supporting cross-functional transformation programs.

Conditions

The company runs background checks at the offer stage for all new hires, which may include criminal background checks for some roles, and needs to process personal information for them.