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Product Manager - Data Platform

Job in Nottingham, Nottinghamshire, NG1, England, UK
Listing for: ENSEK
Full Time position
Listed on 2026-04-29
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 60000 - 80000 GBP Yearly GBP 60000.00 80000.00 YEAR
Job Description & How to Apply Below

About ENSEK

ENSEK builds the cloud‑native SaaS software that’s transforming how energy retailers operate, innovate and manage at scale.

We help retailers lower operating costs, improve billing accuracy for consumers, and enhance customer experience through automation and AI‑driven insight, all underpinned by modern, cloud‑native architecture.

ENSEK is at an exciting inflection point as we scale at pace towards new international horizons. If you’re driven by solving complex, real‑world problems and want to build modern technology that accelerates the global energy transition, you’ll feel right at home with us.

Position Summary:

The Product Manager for Core Data Product owns the Public Data Layer (PDL) as a product — the governed data mart that underpins every ENSEK analytical product, insight dashboard, and the growing external data offer. Our aim is to make ENSEK’s data estate the most reliable, discoverable, and analytically powerful operational dataset in the GB energy retail market. AI tooling will play a growing role in how the team accelerates documentation, automates data quality monitoring, and surfaces analytical insight.

We are looking for someone who has owned a data product or platform at scale, understands what it takes to serve both technical and non‑technical consumers to a defined standard, and is motivated by the commercial opportunity that a high‑quality governed data estate makes possible.

Key accountabilities and responsibilities:
  • Own the strategy, vision, and roadmap for the PDL as a governed data product — engaging external and internal consumers, the Analytics Chapter, and engineering leadership to define, validate, and continuously iterate the direction.
  • Own the commercial narrative for the PDL as an external product offer — defining what ENSEK’s data capability means to an energy retailer’s analytical team, how it is differentiated, and working with commercial partners to validate positioning and identify the investment required to productise it at scale.
  • Make evidence‑based prioritisation decisions, estimating the effort and value of roadmap items, using AI‑powered estimation tools to improve accuracy, and discussing trade‑offs transparently with stakeholders.
  • Define and track key product outcomes — implementing dashboards for real‑time performance visibility, and using data to drive continuous improvement in quality and user experience.
  • Represent users confidently in internal discussions, advocating for research across all user types and leveraging AI‑powered tools to accelerate insight generation at scale.
  • Advocate for product‑led thinking within your team, consult with stakeholders to protect the team from unnecessary directional changes, and champion AI tool adoption.
  • Build long‑term stakeholder relationships, implementing communications strategies and influencing effectively to drive alignment and outcomes.
Key outcomes:
  • Increasing adoption of the PDL by internal and external consumers, with measurable improvement in data consumer outcomes and a reduction in informal workarounds such as direct Databricks queries and Excel‑based reporting.
  • A defined and operating data service — with a published catalogue, a service request process, and an analytics pipeline from the Analytics Chapter — tracked against agreed service levels.
  • New data product opportunities – including the application of predictive models and AI – are identified, defined, evaluated, and when investment criteria are met, instantiated on the product roadmap
  • Roadmap delivered to agreed timelines, with clear evidence of value realised against investment and defined KPIs reviewed regularly with stakeholders.
  • Demonstrable adoption of AI tools to enhance the product offering and improve personal effectiveness.
Skills, knowledge, experience & qualifications:
  • Demonstrable experience owning and delivering a data product, data platform, or governed data mart end‑to‑end within a SaaS or platform environment — with accountability for outcomes, not just delivery.
  • Experience defining and operating a data service: service catalogues, SLAs, consumer onboarding, and managing competing demands across multiple stakeholders.
  • Proven track…
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