At a Glance
- Tasks: Ensure our database systems are reliable, scalable, and support our innovative energy solutions.
- Company: Join Fuse Energy, a cutting-edge renewable energy startup on a mission to revolutionise energy.
- Benefits: Enjoy a competitive salary, equity bonus, and fully expensed tech tailored to you.
- Other info: Dynamic startup culture with opportunities for growth and innovation.
- Why this job: Make a real impact in the renewable energy sector while working with advanced technologies.
- 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.
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.
Qualifications:
- 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 employer: Fuse Energy, LLC
Fuse Energy is an exceptional employer for those passionate about renewable energy and technology, offering a dynamic work culture that fosters innovation and collaboration. With competitive salaries, equity bonuses, and a commitment to employee growth through hands-on experience in cutting-edge projects, team members are empowered to make a meaningful impact in the energy sector. Located in a vibrant startup environment, employees enjoy a supportive atmosphere with benefits like fully expensed tech and meal allowances, making it an ideal place for driven individuals to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Database Reliability Engineer
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We think you need these skills to ace Database Reliability Engineer
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!
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Craft a Tailored Cover Letter:For a full-time role at Fuse Energy, LLC, 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, LLC. 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, LLC
✨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!
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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, LLC!
✨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.
