At a Glance
- Tasks: Ensure our database infrastructure is reliable and scalable while building data pipelines.
- Company: Join a cutting-edge renewable energy startup on a mission to revolutionise energy systems.
- Benefits: Enjoy competitive salary, equity bonuses, and fully expensed tech tailored to you.
- Other info: Dynamic work environment with opportunities for growth and learning.
- Why this job: Make a real impact in the renewable energy sector with innovative technology.
- Qualifications: 3+ years in backend or data-focused engineering, with strong SQL and Python skills.
The predicted salary is between 60000 - 80000 £ per year.
Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system.
We’re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.
We’re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.
Responsibilities
- Own the reliability, performance, and scalability of Fuse's database infrastructure across Postgres and ClickHouse.
- Build and maintain scalable, reliable data pipelines to support analytics, reporting, and product needs.
- Own the design and evolution of analytical schemas, translating business logic into structured, intuitive data models.
- Migrate and transform data from Postgres into ClickHouse, ensuring performance and reliability.
- Develop and maintain DBT models that reflect our business domain and make data easily accessible for teams.
- Implement tests and data quality checks to ensure reliable and trustworthy datasets.
- Identify and eliminate duplicates, improve data consistency, and enforce clean modelling standards.
- Manage all database and infrastructure changes through IaC — minimise direct DB modifications.
Requirements
- 3+ years of experience in a backend engineering or data-focused engineering role.
- Writes the cleanest SQL you've ever seen — proficiency in Python and SQL is non-negotiable.
- Hands-on experience with relational databases, particularly Postgres.
- Experience designing schemas and building data models that reflect real-world business logic.
- Familiarity with DBT or similar data transformation frameworks.
- Strong understanding of data validation, testing, and quality assurance practices.
- Manages all infrastructure through IaC tooling (Pulumi, AWS CDK) — treats the database as code, not a manual system.
- Grasps new business domains quickly — able to translate unfamiliar logic into clean, intuitive data models without hand-holding.
Bonus
- Experience with ClickHouse or columnar databases.
- Familiarity with cloud-based data orchestration tools (Dagster, Step Functions).
- CI/CD practices for data pipelines and transformations.
- Experience operating databases at scale in a production environment.
Benefits
- Competitive salary and an equity sign-on bonus.
- Biannual bonus scheme.
- Fully expensed tech to match your needs.
- Paid annual leave.
- Breakfast and dinner allowance for office based employees.
Database Reliability Engineer in London employer: Fuse Energy
Fuse Energy is an exceptional employer for those passionate about renewable energy and innovative technology. With a vibrant startup culture that encourages creativity and collaboration, employees benefit from competitive salaries, equity bonuses, and generous allowances, all while contributing to a mission that aims to revolutionise the energy sector. Located in a dynamic environment, Fuse offers ample opportunities for professional growth and development, making it an ideal place for individuals looking to make a meaningful impact in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Database Reliability Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Fuse Energy!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Database Reliability Engineer at Fuse Energy.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Fuse Energy.
✨Apply Directly through Our Website
When you find a suitable opening like Database Reliability Engineer at Fuse Energy, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Database Reliability Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Fuse Energy, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Fuse Energy. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Fuse Energy
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Fuse Energy!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.