At a Glance
- Tasks: Design and build analytics platforms to drive data-driven decisions for PlayStation.
- Company: Join Sony Interactive Entertainment, a leader in gaming and innovation.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on creativity and excellence.
- Why this job: Make an impact in the gaming industry with cutting-edge analytics solutions.
- Qualifications: Experience in data modelling, analytics tools, and strong SQL skills required.
The predicted salary is between 60000 - 80000 £ per year.
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.
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 employer: Sony Interactive Entertainment
At Sony Interactive Entertainment, we pride ourselves on being not just the Best Place to Play, but also the Best Place to Work. Our vibrant work culture fosters innovation and creativity, offering employees exceptional growth opportunities within a dynamic technology environment. With a commitment to inclusivity and diversity, we empower our team members to thrive while contributing to the legacy of the PlayStation brand, making it an exciting and rewarding place to advance your career.
Contact Details:
Sony Interactive Entertainment Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Sony Interactive Entertainment on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by diving deep into their analytics platform. Familiarise yourself with dbt and the tools they use. Show them you’re not just a fit for the role, but that you’re genuinely excited about what they do!
✨Tip Number 3
Practice your storytelling skills! Be ready to share specific examples of how you've tackled data challenges in the past. This will help you connect your experience to the role and demonstrate your problem-solving abilities.
✨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 serious about joining the team at Sony Interactive Entertainment.
We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Analytics Engineer role. Highlight your experience with data modelling, dbt, and any relevant BI tools. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about analytics and how you can contribute to our mission at Sony Interactive Entertainment. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any greenfield analytics projects or have examples of data products you've delivered, make sure to include them. We love seeing real-world applications of your skills and how they’ve made an impact.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Sony Interactive Entertainment
✨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, facts and dimensions, and be ready to discuss how you've applied these techniques in past projects. Prepare examples that highlight your ability to create intuitive and robust data models.
✨Familiarise Yourself with dbt Best Practices
Since dbt is a key part of the role, make sure you understand its best practices thoroughly. Be prepared to talk about modularity, reusability, and semantic layering. You might even want to bring along a sample project or two to demonstrate your hands-on experience with dbt.
✨Engage with Business Stakeholders
This role requires close collaboration with business teams, so think about how you've successfully partnered with stakeholders in the past. Prepare to discuss specific instances where you translated complex data requirements into actionable insights, showcasing your ability to balance technical skills with business acumen.
✨Showcase Your Problem-Solving Skills
Be ready to tackle hypothetical scenarios during the interview. Think about how you would approach greenfield analytics projects or improve existing data platforms. Highlight your thought process and decision-making skills, as this will demonstrate your ability to navigate ambiguous data environments effectively.