At a Glance
- Tasks: Transform raw data into actionable insights and build analytics-ready data models.
- Company: Join Utility Warehouse, a leader in the energy sector with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Embrace a culture of collaboration and continuous learning.
- Why this job: Make a real impact by driving data-driven decisions in a dynamic environment.
- Qualifications: Proficient in SQL, data modelling, and stakeholder management.
The predicted salary is between 40000 - 50000 € per year.
Requirements
- 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.
What the job involves
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.
- 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.
Data Analyst (Energy) in London employer: Deepstreamtech
Utility Warehouse is an exceptional employer that fosters a collaborative and innovative work culture, where Data Analysts play a pivotal role in transforming data into strategic insights. With a strong emphasis on employee growth, we offer opportunities for professional development through hands-on experience with cutting-edge technologies and the chance to lead impactful projects. Located in a dynamic environment, our team thrives on diversity and inclusivity, ensuring that every voice is heard and valued.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst (Energy) in London
✨Tip Number 1
Get your networking game on! Connect with professionals in the energy sector on LinkedIn or attend industry meetups. You never know who might have a lead on that perfect Data Analyst role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your SQL queries, data models, and any dashboards you've built. This will give potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Practice your storytelling! Be ready to explain complex data insights in simple terms. Employers love candidates who can bridge the gap between data and business needs—so brush up on your communication skills!
✨Tip Number 4
Apply through our website! We want to see your application directly. Plus, it shows you're genuinely interested in joining our team at Utility Warehouse. Don’t hesitate—hit that apply button!
We think you need these skills to ace Data Analyst (Energy) in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with SQL, Dataform, and Looker. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Projects:If you've led any analytical projects or built data models, share those experiences! We love seeing how you’ve managed the deployment lifecycle and delivered insights that made a difference.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your technical skills and how they relate to the business impact. Remember, we’re looking for actionable insights, so show us you can communicate effectively!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Deepstreamtech
✨Master Your SQL Skills
Make sure you brush up on your SQL skills before the interview. Be ready to discuss your experience with writing optimised, modular SQL and how you've used it in past projects. Practising some common SQL queries can help you feel more confident when discussing your technical expertise.
✨Showcase Your Data Engineering Knowledge
Prepare to talk about your experience with data models and the engineering lifecycle. Highlight any projects where you've built end-to-end analytics-ready data models using Dataform, and be ready to explain how you handle version control with Git/GitHub. This will show that you understand the technical requirements of the role.
✨Communicate Your Insights
Think about how you've translated complex datasets into actionable insights in previous roles. Be prepared to share specific examples of how your analysis influenced stakeholder decisions. This will demonstrate your ability to align your work with business needs, which is crucial for this position.
✨Engage with Stakeholders
Since stakeholder management is key in this role, come prepared with examples of how you've engaged with non-technical teams. Discuss how you've refined broad requests into clear requirements and delivered projects on time. This will highlight your collaboration and communication skills, which are essential for success.
