Utility Warehouse
Utilities
DataProductManager
Neural analysis suggests this role is
optimal for mid candidates.
“Data Product Manager at Utility Warehouse. Skills: Data Product Management, AI infrastructure, Data warehouse. Define one-year roadmap. Plan multi-squad projects”
What You'll Achieve.
Turn data challenges into high-value data products; Ensure data products drive growth; Ensure data products drive efficiency
Industry & Context.
Tackle complex data integration challenges; Solve deep-seated user pain points
What They're Looking For.
Must Have
Solid data literacy, Comfortable with SQL, Understand Modern Data Stack, Chat with engineers about data modeling, Chat with engineers about AI integrations, Full-stack product thinking, Proven experience managing complex internal data products, Data-driven leadership, Use behavioural data, Use predictive modelling, Use machine learning, Commercial smarts, Understand commercial concepts, Smart decision-making, Evaluate third-party vendors, Integrate third-party vendors, Stakeholder management, Work with technical specialists, Work with senior executives, Build relationships, Manage expectations firmly, Deliver value, Strategic customer focus, Understand internal customer deeply, Build deep connections across business, Identify new growth opportunities, Analyze new growth opportunities
Nice to Have
Experience working across complex internal data products
What You'll Do.
Define one-year roadmap
Plan multi-squad projects
Manage complex trade-offs
Own AI infrastructure development
Build self-serve data tools
Bridge gap between engineering teams
Solve user pain points
Manage end-to-end delivery
Make high-stakes decisions
Act as Ambassador for Data team
Keep partners on same page
Manage blockers proactively
Present strategic narratives
Define complex feature sets
Design API integrations
Guide data modeling discussions
How You'll Work.
Team & Collaboration
Multiple squads; Multiple engineering teams; Internal and external partners; Senior leadership; Data squad; Wider business; Technology decisions; Business decisions
Communication Scope
Translate technical architectures; Present strategic narratives
Process & Methodology
Agile delivery, Roadmap, OKRs, KPIs
Full Job 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. 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
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