Data Product Manager at Utility Warehouse

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

07 Sep, 26

Salary

0.0

Posted On

09 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Literacy, SQL, Modern Data Stack, Product Strategy, Technical Business Analysis, Agile Delivery, Data Integration, AI Infrastructure, Self-Serve Data Tools, Stakeholder Management, API Integrations, Data Modeling, Commercial Concepts, Predictive Modeling, Machine Learning, Customer Journeys

Industry

Utilities

Description

Company Description Hi! We're UW. We’re on a mission to take the headache out of utilities by providing them all in one place. One bill for energy, broadband, mobile and insurance and a whole lot of savings! We’re aiming to double in size as we help more people to stop wasting time and money. Big ambitions, to be delivered by people like you. Got your attention? Read on... We put people first. It’s all about you.. We're looking for a Data Product Manager who lives at the intersection of complex tech and commercial strategy. You get a real buzz out of taking knotty, backend data challenges—like aligning disparate schemas or scaling AI pipelines—and turning them into high-value data products that business teams love to use. You aren't just a backlog manager; you’re a collaborative leader who can confidently translate deep technical architectures for executive stakeholders and align multiple squads around a single, cohesive data vision. Job Description We deliver progress. What you’ll do and how you will make an impact. You will tackle the complex data integration challenges of a multi-utility business, combining product strategy, technical business analysis, and agile delivery. Your goal is to make sure our data products aren't just built, but are purpose-built to drive growth and efficiency. Here is what you will get stuck into from day one.. Setting the vision: Define the one-year roadmap for the Data domain, look 3 to 6 months ahead to plan multi-squad projects, manage complex trade-offs, and set clear KPIs and OKRs. Building our Data & AI foundation: Work on building our brand-new data warehouse as a robust data foundation, whilst owning the ongoing development of our AI infrastructure—including Chatbots and Agentic AI. Enabling self-serve journeys: Help build self-serve data tools so colleagues across UW can get the insights they need at their fingertips. Designing great features: Lead the design process for complex features and bridge the gap between multiple engineering teams to solve deep-seated user pain points. Leading big deliveries: Manage the end-to-end delivery of large, multi-quarter initiatives, make high-stakes decisions (like feature deprecation or strategic pivots), and spot and manage any risks along the way. Aligning stakeholders: Act as an Ambassador for the Data team. Keep a complex mix of internal and external partners on the same page, manage blockers proactively, and present clear, compelling strategic narratives to senior leadership. Technical specs & integrations: Define complex, multi-system feature sets, design API integrations, and guide data modeling discussions with engineers to make sure our systems talk to each other seamlessly. We work together. Your team and the people you will work with... You’ll be joining a Data team that is on a serious roll—in fact, we are nearly doubling its size! We are doubling down on our data capability across the entire company. As our new Data Product Manager, you will report to the Head of Data Science and you will be the key link between the Data squad and the wider business. You’ll help our teams prioritise their work, understand their commercial impact, and represent the voice of Data in major technology and business decisions. Qualifications We're looking for a seasoned Product Manager with experience of working across complex, internal data products. To hit the ground running, you’ll bring: Solid data literacy: You are comfortable with SQL and understand the Modern Data Stack (like BigQuery, Dataform, and APIs). You can chat with engineers about data modelling and AI integrations without getting lost. Full-stack product thinking: Proven experience managing complex, internal data products in a fast-growing business. Data-driven leadership: You know how to use behavioural data, predictive modelling, and machine learning to build highly personalised customer journeys. Commercial smarts: You understand commercial concepts like LTV, CAC, Opex, and Capex, and factor them into your product and investment decisions. Smart decision-making: Experience evaluating third-party vendors (build vs. buy decisions) and integrating them into an existing tech ecosystem. Stakeholder management: Experience working with a range of stakeholders including highly technical specialists through to senior executives in commercial functions. You'll be adept at building relationships, managing expectations firmly and delivering value. Strategic customer focus: You understand the internal customer deeply and build deep connections across the business to identify and analyse new growth opportunities. Additional Information Why join UW? We have big ambitions, which means plenty of challenges to tackle and solutions for you to build. We’re looking for people who want to roll up their sleeves and get involved. Our benefits: Competitive salary: We benchmark against the industry and will share the salary openly during our first conversation. Performance bonus: An annual discretionary bonus ranging from 15-40%. Flexible working with a base office in central London Work-life balance: We offer an optional four-day working week (90% pay for 90% impact). Work from anywhere: You can work abroad for up to three weeks, twice every tax year. Holiday: 25 days plus bank holidays (increasing with tenure), with the option to trade up to five days each year. UW discounts: Save on our services and you’ll also get access to 100s of rewards and discounts through Perkbox Future planning: Matched-contribution pension scheme and life assurance (up to 4x salary). Family first: Policies designed to help you and your family thrive. Flexible benefits: An allowance for private health insurance, dental insurance, or gym membership. Sabbaticals: An eight-week paid sabbatical after four years of service. Growth: A dedicated learning and development budget and bi-annual promotion cycles. Inclusion: Join belonging groups that help shape our culture. Events: Company-wide celebrations including the ‘Great Big Get Together’ and our ‘Good Hearted Go-Getter Awards’. Apply now You’ve made it this far... hit apply! We can’t wait to hear from you. Worried you don’t hit every single bit of the criteria? We welcome applications from all backgrounds. If you’re a go-getter with a great heart, get your application in and let’s chat. Claire Fennell will be your point of contact throughout the process. Not sure you meet all the requirements? Let us decide! Research shows that women and members of other underrepresented groups tend not to apply for jobs if they think they may not meet every qualification, when in fact they often do. We provide equal opportunities, a diverse and inclusive work environment, and fairness for everyone. You are welcome to apply no matter your age, disability, gender, marriage or civil partnership status, pregnancy and maternity status, race, religion or belief, or sexual orientation. Please don’t be afraid to ask about what we can do to support your needs. All requests will be carefully and fairly considered. Please note, if you are successful and offered a role at UW, you will be subject to a background check. Where checks are unsatisfactory or incomplete and/or a failure to reveal information relating to convictions that you are required to identify as part of the background checks, could lead to withdrawal of an offer of employment. Employment Status: Full-Time

Responsibilities

You will tackle complex data integration challenges and ensure data products drive growth and efficiency. You will manage the end-to-end delivery of large initiatives and align stakeholders around a cohesive data vision.