Analytics Engineer in London
TRIA London About the role
We're looking for an Analytics Engineer to join our client's high-performing Business Intelligence team, helping to build scalable, high-quality data solutions that power reporting, dashboards and self-service analytics across the business.
Working closely with BI Developers and business stakeholders, you'll design and optimise ETL/ELT pipelines, develop curated data models, and translate business requirements into reliable backend data solutions. This is a fantastic opportunity for someone who enjoys solving complex data challenges and wants to work with modern cloud technologies in a collaborative, forward-thinking environment.
What you'll be doing
- Design, build and maintain scalable ETL/ELT pipelines that deliver reliable, high-quality data.
- Develop curated, business-ready datasets that support reporting, dashboards and self-service analytics.
- Optimise data models, SQL queries and pipeline performance to improve efficiency and scalability.
- Implement data quality, monitoring and governance controls to ensure trusted, accurate data.
- Collaborate with BI Developers to build backend data models that support performant visualisations.
- Work with business stakeholders to understand requirements and translate them into robust technical solutions.
- Contribute to the continuous improvement of the data platform, exploring modern tooling and engineering best practices.
What we're looking for
- Strong SQL skills with experience building and optimising data models.
- Experience designing and maintaining ETL/ELT pipelines.
- Experience working with cloud data platforms (AWS preferred).
- Exposure to data warehousing, data lakes and modern data architecture.
- Understanding of workflow orchestration and automation tools.
- Python experience (including PySpark) is beneficial but not essential.
- Exposure to BI platforms such as Power BI, Tableau or QuickSight, with an understanding of how backend data models support reporting and visualisation.
- Strong communication skills and the ability to work effectively with both technical and non-technical stakeholders.
- A genuine interest in modern data engineering practices and emerging technologies.
The Team
You'll be joining a highly collaborative and engaging team within a business that genuinely invests in its people. Alongside working on modern data technologies, you'll have the opportunity to influence the evolution of the data platform, work closely with experienced BI professionals, and continue developing both your technical and professional skills in a supportive environment.
Please note: This is a backend-focused Analytics Engineering role centred around SQL, data modelling and ETL/ELT development. While you'll work closely with BI Developers, this is not a dashboard or reporting development position.
Your tasks
Design and optimise ETL/ELT pipelines for high-quality data solutions.
Your profile
Strong SQL skills and experience with ETL/ELT pipelines required.
What's also included
Competitive salary, professional development, and a supportive work environment.
Tech stack & ways of working
Analytics Engineer in London employer: TRIA
TRIA is an excellent employer that fosters a dynamic and inclusive work culture in the heart of Bristol. With a strong focus on employee growth, we offer comprehensive training opportunities and a supportive environment that encourages innovation and collaboration. Our competitive salary package, performance bonuses, and generous holiday allowance make TRIA a rewarding place to advance your career in the insurance software industry.
Your perspectives
Tackle complex data challenges using modern cloud technologies and make a real impact.
StudySmarter Expert Advice
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 TRIA!
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 Analytics Engineer at TRIA.
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 TRIA.
Apply Directly through Our Website
When you find a suitable opening like Analytics Engineer at TRIA, 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!
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 TRIA, 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
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How to prepare for a job interview at TRIA
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 TRIA!
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.
Locations
- London
