Senior Analytics Engineer

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 Play Station 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 Play Station brand, a name synonymous with entertainment excellence and creativity.

We are seeking a Senior Analytics Engineer to help design, build, and scale our analytics platform. This is a hands‑on, high‑impact role suited to someone who enjoys greenfield analytics work, has strong opinions on data modelling and architecture, and partners closely with stakeholders to translate business problems into trusted, well‑governed data products.

You will work within the Play Station Partners Platform, delivering global data, reporting, and analytics solutions that support partners worldwide in developing and publishing games and content on Play Station.

Our mission is to deliver timely, scalable, and high‑quality data and insights that enable data‑driven decision‑making, improve operational efficiency, and uncover revenue opportunities. In this role, you will help shape how analytics is delivered across the organisation, from modelling standards and dbt best practices to the creation of trusted, decision‑ready datasets.

Analytics Engineering and Data Modelling

• Design, build, and maintain analytics‑ready data models using dbt, following best practices such as modularity, reusability, and clear semantic layering.
• Lead the development of greenfield analytics assets, from raw source ingestion through to curated, business‑facing models.
• Apply strong data modelling techniques, including dimensional modelling, facts and dimensions, and other appropriate design patterns.
• Own and evolve the analytics layer architecture, ensuring it scales with data volume and business complexity.
• Ensure data quality and trust through testing, documentation, and observability within dbt.

Business Partnership

• Partner closely with business stakeholders, analysts, and product teams to understand requirements and translate them into well‑designed data models.
• Act as a trusted thought partner, helping stakeholders understand what is possible with data and shaping requirements collaboratively.
• Balance technical excellence with pragmatic delivery, focusing on measurable business outcomes.

Platform and Best Practices

• Define and embed dbt standards, including naming conventions, model layering, testing strategies, and documentation practices.
• Contribute to data architecture decisions, including warehouse design, schema organisation, and performance optimisation.
• Improve developer experience through tooling, CI/CD patterns, and modern analytics engineering workflows.
• Maintain deep expertise in the analytics technology stack, ensuring optimal performance and effective feature usage.

• Proven experience delivering data products, analytics, and visualisations using Business Intelligence tools such as Domo, Tableau, Power BI, Qlik, or similar platforms.
• Strong hands‑on experience with dbt, including:
  • Data model design and refactoring
  • Generic and singular testing
  • Documentation and exposures
  • Sources, snapshots, and macros
• Excellent data modelling skills across conceptual, logical, and physical models, including both third normal form and dimensional modelling approaches.
• Advanced SQL skills and experience with modern cloud data warehouses such as Snowflake, Big Query, or Redshift.
• Demonstrated ability to design analytics models that are technically robust and intuitive for business users.
• Experience building greenfield analytics or data platforms, or significantly evolving existing ones.
• Experience with data quality and observability, using dbt or complementary tooling.
• Familiarity with…