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Senior Data Product Manager - 12 months FTC

WTW External598 open roles

Where
London, London, United Kingdom
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Your applicationOpen nowSenior Data Product Manager - 12 months FTCWTW External · London, London, United Kingdom
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The clock on this job

Early applications get read.

13.7% of postings close within 7 days. Measured by our own scanner across the market. WTW External postings stay open a median of 16 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.8%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.6%30 days
  6. 59.1%60 days
This job: posted today

WTW External median: 16 days open

The posting

Job Description

WTW’s Risk & Broking data function is building data products that help colleagues make better, faster, and more consistent decisions. Operating as part of the central data function, the team works with a broad engineering capability, domain specialists, regional data colleagues, and business stakeholders to create products for Great Britain and the global business.

We are looking for a hands-on Senior Data Product Manager who can turn ambiguous business problems into viable data-product opportunities. You will combine product judgement, analytical problem-solving, and technical prototyping to test ideas quickly, establish value, and lead selected products through development, launch, and ongoing improvement.

This is an individual-contributor role for someone comfortable moving between business problems, data, technology, and product delivery. You will not simply write requirements for others. You will explore data, build working prototypes, challenge assumptions, and create the evidence needed to determine whether and how a product should be scaled. This is a 12-month FTC opportunity, based in London, with a hybrid working arrangement requiring 2 days in the office per week. The standard working week is 35 hours.

The Role:

Product discovery and problem definition

  • Work with business stakeholders and domain specialists to understand decisions, workflows, pain points, and opportunities that could be addressed through data products.
  • Convert broad or ambiguous challenges into clear problem statements, target users, desired outcomes, hypotheses, and measurable product objectives.
  • Assess product opportunities based on business value, user need, data readiness, technical feasibility, scalability, and alignment with the broader data-product portfolio.
  • Identify when a request should become a reusable product and when a simpler analytical or process solution is more appropriate.

Prototyping and feasibility

  • Personally build working proofs of concept using tools such as SQL, Python, Databricks, Power BI, AI tooling, and appropriate low-code platforms.
  • Explore and profile data to understand quality, coverage, structure, limitations, and suitability for the intended use case.
  • Use prototypes to test product concepts with users, expose assumptions, and generate evidence before significant engineering investment.
  • Work with data engineers, architects, analysts, and platform specialists to determine how successful prototypes should be industrialised.
  • Ensure prototype work is appropriately transitioned into maintainable, governed, and scalable solutions rather than becoming unsupported production tooling.

Product ownership and delivery

  • Own selected data products from discovery through prototype, development, launch, adoption, and improvement.
  • Define product vision, outcomes, scope, roadmap, success measures, and priorities.
  • Translate user and business needs into clearly articulated product requirements, data requirements, and acceptance criteria.
  • Make day-to-day prioritisation and scope decisions within the agreed product strategy.
  • Balance speed of experimentation with data quality, architecture, governance, security, and maintainability.
  • Partner closely with engineering while retaining clear accountability for the problem, user outcome, and product value.

Stakeholder collaboration

  • Build effective relationships with business stakeholders, domain specialists, engineers, architects, analysts, and regional data colleagues.
  • Facilitate structured product conversations that distinguish real user needs from proposed solutions.
  • Explain technical concepts and analytical findings clearly to non-technical stakeholders.
  • Create transparency around assumptions, dependencies, risks, product choices, and expected outcomes.
  • Help establish consistent data-product practices across the central function.

Product performance and improvement

  • Define and monitor measures covering product use, user outcomes, data quality, operational efficiency, and business benefit.
  • Use feedback and product evidence to improve, scale, reposition, or stop products.
  • Ensure product documentation, ownership, lineage, intended use, and limitations are clear.
  • Contribute reusable methods, templates, prototypes, and lessons to the wider data-product capability.

Qualifications

What you'll bring:

  • Proven experience across data, analytics, technology, or digital products, with a strong track record of owning and delivering data-enabled products or solutions.
  • Strong evidence of solving ambiguous business problems and converting them into practical, evidence-based solutions.
  • Hands-on ability to interrogate data and build working prototypes using several of SQL, Python, Databricks, Power BI, AI tooling, or low-code tools.
  • Experience undertaking product discovery, defining user needs, setting product outcomes, prioritising work, and collaborating with engineering teams.
  • Ability to assess data quality and technical feasibility without relying entirely on others to interpret the underlying data.
  • Experience taking at least some products or analytical solutions beyond ideation into sustained use.
  • Strong written and verbal communication skills with business, domain, data, and technology stakeholders.
  • Ability to work independently while building alignment across a complex organisation.

Desirable experience

  • Commercial insurance, insurance broking, specialty insurance, claims, placement, portfolio analytics, or underwriting experience.
  • Experience with data mesh, domain-oriented data products, common data models, data contracts, metadata, and data governance.
  • Experience industrialising analytical prototypes with data-engineering and architecture teams.
  • Experience integrating generative AI or machine learning into business products.
  • Familiarity with regulated environments and the responsible use of commercially sensitive data.

What we offer:

Enjoy a benefits package designed to help you thrive, both professionally and personally. You'll receive 25 days of annual leave plus an extra WTW day to relax and recharge. Our comprehensive health and wellbeing offering includes private healthcare, life insurance, group income protection, and regular health assessments, all giving you peace of mind. Secure your future with our defined contribution pension scheme, featuring matched contributions up to 10% from the company.

We support your growth and balance with hybrid working options, access to an employee assistance programme, and a fully paid volunteer day to make a difference in your community. On top of these, you can opt into a variety of additional perks including an electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and much more. Start making the most of your career and wellbeing with a range of benefits tailored for you.

Equal Opportunity Employer

We’re committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email [email protected]

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