Data Product Owner

Yorkshire Water
Bradford
10 months ago
Applications closed

Related Jobs

View all jobs

Product Data Scientist

Product Manager

Data Science Manager

Data Science & AI Consultant

Senior DataOps Engineer

Machine Learning and AI Engineering Lead

Data Product Owner

Salary & benfits: £50,972 - £73,854 + car allowance (or £2,500 cash incentive) + attractive pension + annual bonus + 26 days holiday.

Location: Bradford, Buttershaw and hybrid work arrangement (Avg. 1 day per week in office)

We have an exciting opportunity for a Data Product owner to join the data department at Yorkshire Water and help us use data to deliver a better and more efficient service for our customers. Could this be you?

million people in Yorkshire rely on the services we provide. Every day 2 million homes across the region receive over 1 billion litres of drinking water, delivered, collected, and recycled through 50,000 miles of pipework. Protecting public health and the environment is at the heart of what we do.

New environmental legislation, unprecedented levels of investment and changing expectations from customers means that this is an exciting time to discover opportunities within the water industry. Data and technology are a key part of how we plan to meet the changing expectations of customers and regulators.

Yorkshire Water has a significant data footprint and partnerships with global organisations like Microsoft, SAP, Databricks, and ESRI. Our data is spread across the county of Yorkshire, with over 1 million real time data points monitoring reservoirs, treatment facilities, pipework, and pumps. Data is key to optimising what we do and how we do it and planning for the future of Yorkshire.

Data roles at Yorkshire Water are all about leveraging value from our vast data estate, be it exploring problems using innovative data science approaches, developing robust technical solutions which are relied upon every day, or creating intuitive dashboards that aid in strategic decision-making; there’s plenty of opportunities to utilise and develop your data skillsets whilst making a real impact on improving service to our customers and the environment.

As our Data Product Owner, you’ll be accountable for the following:

Contribute to the delivery, and maintenance of the team strategy, vision, purpose, goals, objectives, and measures.  Support the delivery, and maintenance the Target Operating Model for the team.  Develop and manage the Roadmaps & Product backlogs.  Develop, define and prioritise and stories in support of products and manage increments and change.  Clearly communicate products/features/iterations and stories to internal (Team) and external stakeholders (Business).  Identify, manage, and maintain relationships with key stakeholders across the business and ensure needs are represented in the Products.  Maintain a clear view of external trends, opportunities, and technologies within the domain across the utility sector and beyond.  Identify and manage risks and issues.  Provide assurance for the quality, sustainability, and effectiveness of deliverables for all solutions within their business services.  Influence the strategic technology/data decisions through feedback and collaborative working with all relevant Tech stakeholders  Provide coaching and development of colleagues to create resilience and succession.  Identify opportunities for innovation through existing or future data capabilities.  Drive continuous improvement to proactively identify & remove waste from processes & activities. 

What skills are we looking for?

Essential

Proven track record, preferably in the utilities sector or asset management sector, of undertaking a Product Owner Role  Experience of Product Ownership or Product Management in a scaled agile environment.  Experience of developing and maintaining effective internal and external relationships at executive or senior levels within an organisation.  Ability to demonstrate relentless drive, energy and determination to deliver sustainable outperformance for YW that rigorously achieves against demanding competitive industry benchmarks and metrics from other organisations.  Ability to prioritise and execute tasks in a dynamic, changing environment and make sound decisions in emergency situations.  Excellent interpersonal, written and oral communication skills.  Ability to absorb complex technical information and communicate effectively to all levels, both technical and non-technical audiences.  Ability to develop and work in a team-oriented, collaborative environment.  Ability to pick up and own issues or projects on behalf of the management team.  Strong organisation and personal management skills.  Possess a strong sense of purpose and proactively seek responsibility and ownership.  Creativity and lateral thinking.  Highly motivated and self-reliant with a personal drive for continuous development and demonstrates a strong customer service ethos.  Proven analytical and problem-solving abilities.  Ability to understand enterprise solutions.  High standards of integrity & ethics. 

Desirable

Lean Six Sigma  Scaled Agile/Agile methodologies  Experience of SaaS, PaaP, IaaS, DaaS 

We embrace a flexible working model, where our hybrid setup typically requires an average of one day in the office per week. During quieter periods, this may decrease, or it could be slightly more when collaborative efforts or meeting deadlines demands it. The office is readily accessible in working hours for those who prefer a physical office environment.

Apply now to find out what a career in tech with Yorkshire Water could offer you!

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.