Data Analyst at Utility Warehouse

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

28 Jun, 26

Salary

0.0

Posted On

30 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, BigQuery, Dataform, Looker, Mixpanel, Analytics Engineering, CI/CD, DevOps, Git, Github, Unit Testing, Performance Engineering, Stakeholder Management, Data Storytelling, Data Modeling, Version Control

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 on the hunt for talented Data Analysts to join the team as we grow our business. Our vision is simple, an effortlessly rewarding experience where customers only need to tell us something once. We are redesigning our digital landscape to ensure that being multi-service means being seamless, whether that’s a lightning-fast onboarding journey, automated home moves, or proactive push notifications. We are investing heavily on solving root causes, not just symptoms. We are looking for product-minded talent to own these journeys, turning complex utility data into simple, transparent, and high-value digital experiences that customers enjoy using. Job Description We deliver progress. What you’ll do and how you will make an impact. As a Data Analyst at Utility Warehouse, you will own the complete "Data-to-Insight" value chain for single projects. This role combines the technical skills to build production-grade data pipelines with the soft skills to manage stakeholders and drive domain-specific decisions. You are the core "builder" of the team. This role marks the transition from implementing to designing. The defining characteristic of this level is the independent management of the deployment lifecycle. You will be responsible for ensuring that data transformation logic is not just correct, but reproducible, tested, and version-controlled. You will not just report on data; you will build and maintain the analytics layer data models and automated pipelines that power our company’s decision-making engine. You will leverage modern data stack technologies (SQL, BigQuery, Dataform, Looker, Mixpanel) to transform raw data into high-value strategic assets, ensuring scalability and accuracy across business functions. Your responsibilities will include: Analytics Engineering (Dataform/dbt): Build and maintain end-to-end analytics-ready data models in Dataform, independently handling complex logic and transformations. CI/CD & DevOps (Data version control): Apply version control (through tools like Git & Github) and unit testing practices to analytics models, to ensure data assets are stable, reproducible, and ready for deployment. Performance Engineering: Write optimised SQL, proactively tuning for performance (cost & runtime) and addressing alerts about data quality. Ownership: Independently plan and execute medium-to-large requests through to completion; identify and proactively address tech debt. Actionable Insight: Translate complex data into actionable business insights. Move beyond "what happened" to explain "why it happened" and recommend "what to do next." Dashboards/Reporting: Build visual self-serve dashboards and reports for users to access KPIs / metrics and explore/analyse pre-built data set. Stakeholder Management: Manage the full request lifecycle. Actively engage with stakeholders to refine broad requests into clear requirements, providing accurate estimations and delivering within agreed timelines. Domain Ownership: Develop deep knowledge of a specific domain (e.g., Marketing, Product, Finance). Understand the impact of key metrics on the business and participate in defining team goals based on this knowledge. Qualifications Here's some of the key skills and experience we're looking for you to bring: Technical & Data Engineering Mastery: Proven experience in writing optimised, modular SQL (Intermediate - advanced proficiency) Experience of building end-to-end, analytics-ready data models in Dataform, underpinned by a strong grasp of the engineering lifecycle (including Git/GitHub version control, merge conflict resolution, and automated unit testing). Analytics Architecture & Delivery: Solid expertise in building reusable LookML code within Looker and the ability to independently lead medium-to-large analytical projects—from selecting the right tool for the job (e.g. Looker vs Mixpanel) to providing accurate estimations and hitting delivery timelines. Commercial Impact & Domain Knowledge: A track record of aligning analysis with business needs and translating complex datasets into actionable insights that influence stakeholder decisions, Ideally you will have experience in regulated utility or a similar high-volume consumer industry. Operational Excellence & Collaboration: Experience in maintaining high data standards through observability (configuring freshness and quality alerts) and producing traceable documentation (Data Dictionaries), with a demonstrated ability to support non-technical teams through clear data storytelling UW skills and competencies Prioritisation Collaboration Communication Attention to Detail Project Management Additional Information Our Interview Process: Application Short online SQL Test (10 minutes) Recruitment Screen (30 minutes) SQL Programming test (up to 45 minutes) Hiring Team Interview (1 hour) Final Presentation (1 hour) So why pick UW? We’ve got big ambitions so there’s going to be plenty of challenges. There are also a lot of benefits: An industry benchmarked salary. We’ll share it during your first conversation. Hybrid working, with 1-2 days in the office. (We’re definitely open to discussing flexible working arrangements) Discount on our services and you get our coveted Cashback Card for free. You’ll also get access to 100s of rewards and discounts through Perkbox A matched contribution pension scheme and life assurance up to 4x your salary. You can also access free mortgage advice and a financial wellbeing tool. Family-friendly policies, designed to help you and your family thrive. Discounted private health insurance, access to an Employee Assistance line and a free Virtual GP. Our wellbeing app Unmind supports your mental health. Belonging groups that help UW shape an even more inclusive future. A commitment to helping you develop your career journey through learning, coaching and new experiences Apply now! You’ve got this far... Hit apply - we can’t wait to hear from you! Worried you don’t hit all the criteria? We welcome applications from diverse and varied backgrounds so get your application in and let’s chat! Beth Rodgers will be your point of contact throughout the recruitment 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

The Data Analyst will own the complete "Data-to-Insight" value chain for projects, building and maintaining analytics layer data models and automated pipelines using modern data stack technologies. Responsibilities include analytics engineering, CI/CD implementation, performance tuning, and translating complex data into actionable business insights.