Senior Data Product Manager in Maidenhead

This is a pivotal, foundational role within RWS Product & Technology, as we build out a world-class Data and AI capability. As a Data Product Manager, you will be instrumental in transforming our enterprise data into high-value, governed data products. This isn’t just about managing data; it’s about applying product thinking to data assets to improve decision-making, enable advanced analytics, and lay the critical groundwork for our future AI and agentic AI architectures.

You will own a specific domain of data, treating it as a product—defining its roadmap, ensuring quality, and maximizing its business impact. This opportunity is unique because you will be a founding member of the Data Product Management function, shaping the standards, processes, and tools we use to establish a federated, data-driven culture built on modern concepts like Data Mesh. You will report to the VP of Data, partnering closely with Data Engineers, Data Scientists, and business stakeholders across the organization to ensure our data delivers measurable business value.

Key Responsibilities

• You will own the end-to-end lifecycle of high-value data products, focusing on business impact and technical excellence.
• Define and Develop Data Products: Treat specific data domains (e.g., Customer, Inventory, Financials) as products, defining their value proposition, user personas, and iterative release roadmap.
• Bridge Stakeholder Gaps: Act as the primary liaison between Data Engineering teams and business domain experts, translating complex business needs into clear, deliverable data requirements.
• Drive Self-Service Adoption: Create and manage semantic layers, providing clear documentation and tooling (like Looker/BigQuery reference queries) to enable business users to confidently explore and use data products without constant central team support.
• Enable AI and Analytics: Design data products to seamlessly support downstream consumers, from foundational reporting to complex ML models and emerging agentic AI architectures (e.g., Model Context Protocol).
• Advocate for Data Mesh Principles: Ensure your data products adhere to core standards: Discoverable, Addressable, Trustworthy, Self-describing, Interoperable, and Secure (DATSIS).
• Establish Data Contracts and Quality: Build and enforce "data contracts" between producers and consumers to guarantee stable schemas, semantics, and predictable consumption, owning accountability for data quality across your domain.
• Monitor and Optimize Value: Track key metrics including data product adoption, usage, quality (Service Level Objectives/SLOs), and the associated costs (FinOps), ensuring a high return on investment.

Skills & Experience

• Accomplished Data Product Management: Proven experience applying product management principles (roadmapping, user stories, KPIs) specifically to data assets.
• SQL Fluency: Advanced competency in writing and optimizing complex SQL queries to validate, prototype, and understand data structures.
• Data Mesh & Federated Architecture: Strong foundation or demonstrable experience with modern data governance and architecture concepts, such as Data Mesh or federated data management.
• Data Quality Ownership: Direct experience defining, implementing, and monitoring data quality measures, establishing clear Service Level Objectives (SLOs) for data products.
• Diverse Data Usage Patterns: Understanding of how data is consumed by different personas (analytics, reporting, business intelligence, and ML/AI models).
• GCP Data Suite Proficiency: Strong working knowledge of Google Cloud Platform data services, including BigQuery, Cloud Storage, Cloud Pub/Sub.
• Strategic & Collaborative Mindset: The ability to promote a culture of data ownership and quality across business teams rather than centralizing all responsibility.

Nice to Have

• Ecosystem Experience: Familiarity with the broader GCP analytics ecosystem (e.g., Looker, Dataplex, Dataflow).
• AI Integration Experience: Exposure to frameworks for managing model context or facilitating data flow into AI/ML models (e.g., Model Context Protocol, Vertex AI integration).
• Coding: Proficiency in a programming language like Python for prototyping or tooling.
• Organisational Complexity: Experience delivering success in a complex, global company undergoing significant transformation.

Life at RWS - If you like the idea of working with smart people who are passionate about growing the value of ideas, data and content by making sure organizations are understood, then you’ll love life at RWS. Our purpose is to unlock global understanding. This means our work fundamentally recognizes the value of every language and culture. So, we celebrate difference, we are inclusive and believe that diversity makes us strong. We want every employee to grow as an individual and excel in their career.

In return, we expect all our people to live by the values that unite us: to partner, putting clients first and winning together, to pioneer, innovating fearlessly and leading with vision and courage, to progress, aiming high and growing through actions and to deliver, owning the outcome and building trust with our colleagues and clients.

RWS embraces DEI and promotes equal opportunity, we are an Equal Opportunity Employer and prohibit discrimination and harassment of any kind. RWS is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at RWS are based on business needs, job requirements and individual qualifications, without regard to race, religion, nationality, ethnicity, sex, age, disability, or sexual orientation. RWS will not tolerate discrimination based on any of these characteristics.

Get the 3Ps right - Partner, Pioneer, Progress - and we’ll Deliver together as RWS.