At a Glance
- Tasks: Build and improve data models to support lending decisions and enhance analytics culture.
- Company: Join Lendable, a fast-growing fintech unicorn transforming credit access.
- Benefits: Flexible working, health coverage, office meals, and employee referral bonuses.
- Other info: Collaborative environment with excellent career growth and social opportunities.
- Why this job: Make a real impact in a dynamic team while shaping the future of finance.
- Qualifications: Strong data modelling skills and experience with ELT pipelines and cloud data warehouses.
The predicted salary is between 50000 - 60000 £ per year.
hackajob is collaborating with Lendable to connect them with exceptional professionals for this role.
About Lendable
Lendable is on a mission to build the world's best technology to help people get credit and save money. We’re building one of the world’s leading fintech companies and are off to a strong start:
- One of the UK’s newest unicorns with a team of just over 700 people
- Among the fastest-growing tech companies in the UK
- Profitable since 2017
- Backed by top investors including Balderton Capital and Goldman Sachs
- Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)
So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days.
We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.
Join us if you want to:
- Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1
- Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo
- Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting
About the role
We’re looking for an analytics engineer to contribute to the analytical foundation of the UK Motor team, a rapidly-growing area of the business. You’ll work closely with analysts, product teams, backend engineers, and business stakeholders to improve how data is structured, transformed, and consumed across the company. The role is fundamentally about building a strong analytical foundation: making it easier for teams to move from question to insight quickly, while maintaining high standards around data quality, scalability, and maintainability. You'll contribute to the modelling layer, help improve how the business works with data, and support the team in keeping our warehouse a reliable, strategic asset for the business.
What you’ll be doing:
- Building and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting.
- Championing standards and contributing to the improvement of our analytics engineering culture.
- Supporting and collaborating with analysts at different technical levels, helping translate requirements into robust pipelines.
- Helping triage and resolve issues that affect the analytics pipeline or reduce trust in downstream datasets, and contributing ideas to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.
Our modern data stack
You’ll work with a modern analytics stack centred around SQL, Snowflake, dbt, Fivetran and Claude.
What we’re looking for:
We’re looking for someone with solid analytics engineering fundamentals and the ability to apply them pragmatically in a fast-moving environment and explain tradeoffs to stakeholders with varying technical depth. More specifically, we’re looking for:
- Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability.
- Strong experience with ELT pipelines and transformation at scale, ideally using dbt.
- Experience with Snowflake or another modern cloud data warehouse.
- Proactiveness in raising areas of data workflows that could be improved and suggesting solutions.
- A collaborative working style and clear communication across technical and non-technical stakeholders.
- Comfort using AI tools effectively to move faster, improve quality, and strengthen day-to-day analytical and engineering workflows.
Interview process:
- Initial call with an engineer
- 15 minute Cognitive Assessment
- Onsite or Video Interview lasting 90 minutes, comprising of:
- Introduction of the team and kind of work you could be doing daily
- Interactive architecture/design exercise
- Questions you may have about the company, role, etc.
- A 60 minute chat with this role's primary stakeholders
- Cultural/behavioural questions
- Product mindset and ability to collaborate and communicate
Life at Lendable:
- Winning team: the opportunity to scale up one of the world’s most successful fintech companies
- Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites
- Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls
- Health coverage: support for your physical and mental wellbeing, including private health cover
- Retirement & savings: long-term financial wellbeing through retirement savings plans
- Employee referral programme: earn a competitive bonus when you refer successful new team members
- Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations
- Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations
Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer (London)
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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 Lendable!
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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 Lendable.
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We think you need these skills to ace Analytics Engineer (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 Lendable, 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 Lendable. 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 Lendable
✨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 Lendable!
✨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.
