Staff Data Architect

Tbwa Chiat/Day Inc
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer: Architect Scalable Data Platforms

Staff Data Engineer

Staff Data Engineer...

Staff Data Engineer

Staff Data Engineer

Staff Data Engineer

PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation5, PlayStation4, PlayStationVR, PlayStationPlus, acclaimed PlayStation software titles from PlayStation Studios, and more.

PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Corporation.

Are you passionate about technology that enables the use of data to gain insights, improve customer experience, and drive revenue? With over 180 Million highly engaged customers in 109 countries, Sony Interactive Entertainment (SIE) is committed to using data to understand our Players and Partners, and enable the enterprise to make data driven decisions.

What you will be doing

As a member of the architecture team, you will collaborate with other architects to maintain a structured architecture across a number of domains, including Commerce, Partner (Game Publishers/Developers), Accounts and Identity, Customer Care, IT, and Enterprise Applications. In your role as a Data Architect, you will use your expertise to maximise value from data for our Players, Partners, and Operators.

  • Data Architecture:Manage the data architecture across our data platforms.

Translate business requirements into conceptual and logical data models. Work with the engineering teams to ensure the physical data models are aligned with the logical & conceptual data model.

Ensure data is efficiently organised and presented across data lakes and data warehouse platforms to drive business insights, analytics, data science and machine learning use cases.

  • Data Architecture Standards:Maintain and enhance the logical and physical data modeling standards and guidelines. Align them with industry best practices to ensure the data model is scalable and efficient to meet our business needs.

Promote the adoption of the data architecture standard and guidelines with the engineering teams.

  • Data Management:Maintain data documentation including data dictionaries, metadata, and high level data lineage. Ensure the data architecture is compliant with SIE Data Governance and Security policies.
  • Integration Architecture:Define logical data flows. Reuse existing design patterns and define new design patterns in collaboration with engineering where necessary.
  • Architecture Deliverables:Deliver high-quality architecture documentation that clearly explains the solution and the rationale behind the decisions made. Ensure the documentation is comprehensible to the target stakeholders, such as Product Management and Engineering teams.
  • Architecture Governance:Contribute and drive the adoption of the architecture standards, patterns and policies across engineering teams in the data group and other teams in SIE.
  • Collaborate:Build a strong working relationship with architects and engineering teams across SIE, especially in the data domain. Take an active role in contributing to the effectiveness of the architect community.

What are we looking for

  • Minimum 5 years of commercial Data Warehousing experience with at least 2 years of data modeling experience.
  • Proficiency in data management concepts, practices and procedures; as well as extensive knowledge of data integration, data quality, multi-dimensional design and ETL tools, processes and methodology.
  • Experience of designing and implementing Data Lake solutions.
  • Experience of corporate data governance and compliance including GDPR and data protection/privacy rules.
  • Experience of working with data science and machine learning teams, ensuring the data can be efficiently used to drive DS & ML use cases.
  • Demonstrable experience of working with data science and machine learning teams on feature engineering and feature stores.
  • Demonstrable knowledge of the use of Agile methods, and working closely with product managers and engineering teams. Ensuring the solution meets the requirements and is deliverable.
  • Demonstrable knowledge of architecture governance using principles, policies, views and viewpoints.
  • Demonstrable knowledge of Business Intelligence & Analytics industry and leading industry standards.
  • Ability to communicate complex technical issues to different audiences from technologists to senior leadership team members.
  • Ability to build rapport and influence through collaborative leadership.

SIE Data Organizations Technology Stack

High level summary of the key applications and platforms used by the SIE Data Group:

  • Hosting:Almost all of our key applications and platforms are hosted on AWS.
  • Data Integration:Ab Initio (hosted on AWS) & Databricks (SaaS).
  • Data Streaming:Kafka and Flink.
  • Data Warehouse:Snowflake (SaaS).
  • Data Lake:AWS Lakeformation, Glue and some customised components.
  • Reporting Platforms:MicroStrategy, Domo, Imply and Tableau.
  • Web Analytics & Telemetry:Adobe Experience Platform.
  • Data Science Platform:Databricks, Tecton & Airflow.

#LI-GM1

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.

PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Apply for this job

* indicates a required field

First Name *

Last Name *

Email *

Phone *

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

LinkedIn Profile

Website

What are your salary expectations? *

What is your current notice period? * Select...

Depending upon where you are currently living, it may be necessary for you to relocate if you are appointed to this role. In order that we can ensure that we promptly provide any appropriate relocation support, please confirm the location at which you currently reside. * Select...

If other, please provide.

Have you previously worked for Sony? * Select...

How did you hear about this job? * Select...

If Employee Referral, please provide the name of the employee who referred you.

Do you wish to be considered for other roles? Select...

Do you hold the right to work in the UK? * Select...

If Other, please provide additional information regarding your right to work in the UK.

Would you like to stay connected with us? * Select...

Question: Stay Connected for Future Opportunities?

Thank you so much for considering a role with us! Should this position not be the perfect fit right now, we would be excited about the chance to explore future opportunities with you. By selecting "Yes," you’ll allow us to keep your details on file for the next 24 months. This means we can reach out to you about other exciting roles that may fit your skills and interests as they come up. We’re eager to stay connected!

We take your privacy seriously and will ensure your information is securely stored and used only for recruitment purposes, as outlined in our (Candidate Privacy Notice). Please take a moment to review it for more details.

UK Diversity & Inclusion - Voluntary Equal Opportunity Monitoring

Sony Interactive Entertainment Europe Limited (‘SIEE’) is committed to ensuring that all job applicants and members of staff are treated equally, without discrimination because of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age. Collecting diversity data is intended to help SIEE maintain equal opportunities best practice and identify barriers to workforce equality and diversity. Please read this notification and consent before you decide whether to submit your diversity data in the survey below.

SIEE will treat all survey responses in the strictest confidence, and our personnel with decision-making role in the recruitment process can only see aggregated reports on the results of the survey and cannot allocate these aggregated reports to individual applicants. There is no obligation on you to provide diversity data, SIEE will treat all applicants the same regardless of whether they provide diversity data or not, and any responses to the survey will not affect our decision on your application.

You can withdraw your consent at any time. The withdrawal of your consent does not affect the lawfulness of the processing of your diversity data based on your consent before its withdrawal.

Please tick this box to confirm that you explicitly consent to providing the diversity data below, including the below sensitive information on your racial or ethnic origin, your sexual orientation and your gender identity, and to SIEE using this data as Select...

How would you describe your gender identity? Select...

How would you describe your nationality and/or ethnicity? Select...

Do you identify as transgender? Select...

How would you describe your sexual orientation? Select...

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.