At a Glance
- Tasks: Design and build analytics platforms to drive data-driven decisions for PlayStation.
- Company: Join Sony Interactive Entertainment, the powerhouse behind PlayStation.
- Benefits: Competitive salary, inclusive culture, and opportunities for growth.
- Other info: Dynamic work environment with a focus on innovation and collaboration.
- Why this job: Make a real impact in gaming by shaping analytics for global partners.
- Qualifications: Experience in data modelling, analytics tools, and strong SQL skills required.
The predicted salary is between 60000 - 80000 ÂŁ per year.
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.
About the Role 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 PlayStation Partners Platform, delivering global data, reporting, and analytics solutions that support partners worldwide in developing and publishing games and content on PlayStation. 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.
What You Will Be Doing
- 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.
Required Skills
- 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, BigQuery, 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 orchestration tools such as Airflow, Dagster, or Prefect.
- Experience with semantic layers, metrics frameworks, or analytics consumption patterns.
- Exposure to data governance, access control, or analytics enablement at scale.
- Experience mentoring or supporting junior analytics engineers or analysts.
- Strong track record of partnering effectively with business teams to deliver outcomes.
- Undergraduate degree in a related field, or an equivalent combination of education and experience.
Desirable Experience and Attributes
- Comfort operating in ambiguous or evolving data environments.
- Strong focus on clean design, maintainability, and long‑term sustainability, not just speed of delivery.
- Pride in building trusted data assets that are widely adopted and valued.
- Ability to be opinionated yet pragmatic, clearly explaining trade‑offs and adapting when required.
- Experience maintaining high technical delivery standards, including documentation and end‑user self‑service enablement.
- Collaboration with business, product, and engineering teams to deliver scalable and flexible solutions.
- Ongoing support for users who rely on analytics products for decision‑making.
Nice to Have
- Extensive experience with Domo.
- Hands‑on experience with Snowflake.
- Exposure to web technologies such as JavaScript, HTML, and CSS.
- Experience in web analytics or related domains.
- Knowledge of statistical methodologies.
- Exposure to data science or advanced analytics use cases.
- Experience developing on AWS.
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Senior Analytics Engineer in London employer: PlayStation Global
Contact Detail:
PlayStation Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Sony Interactive Entertainment. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repository showcasing your analytics projects. This is your chance to demonstrate your data modelling prowess and how you tackle real-world problems.
✨Tip Number 3
Prepare for the interview by diving deep into SIE's products and services. Understand their analytics needs and think about how your experience aligns with their mission. Tailor your examples to show you're the perfect fit!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the SIE team.
We think you need these skills to ace Senior Analytics Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior Analytics Engineer role. Highlight your experience with data modelling, dbt, and any relevant analytics tools. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of past projects where you've designed or built analytics platforms. We love seeing real-world applications of your skills, so don’t hold back on the details that demonstrate your impact!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use clear language to explain your experience and how it relates to the role. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website: Don’t forget to submit your application through our official website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at PlayStation Global
✨Know Your Data Modelling Inside Out
As a Senior Analytics Engineer, you'll need to showcase your expertise in data modelling. Brush up on dimensional modelling and be ready to discuss your experience with dbt. Prepare examples of how you've designed analytics-ready data models and the impact they had on decision-making.
✨Showcase Your Business Partnership Skills
This role requires close collaboration with business stakeholders. Think of specific instances where you translated complex data requirements into actionable insights. Be prepared to explain how you balance technical excellence with delivering measurable business outcomes.
✨Familiarise Yourself with the Tech Stack
Make sure you're well-versed in the analytics technology stack mentioned in the job description, especially dbt and cloud data warehouses like Snowflake or BigQuery. Highlight any hands-on experience you have with these tools and how you've used them to improve data quality and observability.
✨Prepare for Technical Questions
Expect to face technical questions that assess your SQL skills and understanding of analytics architecture. Practice solving problems on the spot and explaining your thought process clearly. This will demonstrate your ability to think critically and adapt to evolving data environments.