At a Glance
- Tasks: Own our data warehouse, translating business needs into actionable models and numbers.
- Company: Join a dynamic fintech company with an AI-first approach and a collaborative culture.
- Benefits: Competitive salary, 30 days holiday, health insurance, and hybrid working options.
- Other info: Opportunity for career growth and to work with cutting-edge AI tools.
- Why this job: Make a real impact by shaping data strategies in a fast-paced environment.
- Qualifications: 4+ years in analytics engineering, strong SQL and dbt skills required.
The predicted salary is between 70000 - 90000 £ per year.
The role involves day-to-day ownership of our data warehouse, focusing on analytics engineering with a strong business emphasis. There is no data engineering or data science in the role. The main responsibility is translating how the business works into models and numbers that can be acted upon.
Key responsibilities include:
- Using dbt on BigQuery for model design, data quality, and maintaining the source-of-truth layer.
- Joining the business together across systems, including CRM, ledgers, operational tools, and compliance systems.
- Leading the Lightdash to Omni migration and owning the semantic layer.
- Handling regulatory and compliance reporting, including recurring submissions against fixed deadlines.
- Partnering with Finance, Product, Operations, Compliance, Sales, and the executive team to understand the decision behind each request.
- Implementing quality-of-life automations to remove manual steps and return data to existing tools.
The role operates within a lean team with a wide remit and high pace, managing multiple unrelated requests simultaneously. You will set conventions, definitions, and standards, establishing what is being asked as part of the work. Daily access to the Head of Data is provided, with an expectation of reaching independence quickly.
Essential skills:
- Senior-level dbt experience, having owned a project end to end.
- Senior-level SQL proficiency, with a focus on complex, clean, and performant queries.
What matters most: Technical skill is essential, but business understanding distinguishes candidates. You should understand how systems interact commercially and design entities that match business thinking. You are comfortable being treated as a peer and can explain your work clearly to non-data professionals.
Desirable skills:
- Experience with Omni due to the upcoming migration.
- Familiarity with regulated environments such as payments, banking, EMI, or crypto.
- Technical literacy beyond SQL, including knowledge of APIs and some Python or JavaScript.
- Experience with workflow automation tools (n8n, Zapier, etc.) and reverse ETL.
Not required: Data engineering, data science, streaming infrastructure, machine learning, or software engineering.
Background: 4+ years in analytics engineering or a comparable role. A numerate or analytical education is beneficial, but no specific discipline is required.
Interview Process: Three stages: a technical and behavioural conversation with the Head of Data, a session with leads from the teams you would work alongside, and a conversation on judgement and reasoning.
What's in it for you:
- Salary range: £70,000 - £90,000pa
- 30 days holiday, plus 4 wellbeing days and 1 volunteering day
- Salary sacrifice pension scheme
- AXA health insurance
- Income protection
- Life assurance
- Hybrid working (1-2 days in the office)
- Enhanced parental leave
- Salary sacrifice creche and cycle to work scheme
- Frontier AI tool stack
Senior Analytics Engineer in London employer: BCB Group
BCB Group is an exceptional employer, offering a dynamic work environment at the forefront of the rapidly evolving cryptocurrency industry. With a strong focus on personal growth and empowerment, employees are encouraged to thrive alongside the business, benefiting from a collaborative culture that values innovation and excellence. The company provides a robust benefits package, including generous annual leave, mental health days, and comprehensive healthcare options, making it an attractive place for talented individuals looking to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics 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 BCB Group!
✨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 Senior Analytics Engineer at BCB Group.
✨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 BCB Group.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Analytics Engineer at BCB Group, 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 Senior Analytics 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 BCB Group, 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 BCB Group. 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 BCB Group
✨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 BCB Group!
✨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.
