At a Glance
- Tasks: Transform and model data using SQL and Python to build efficient data workflows.
- Company: Join Lendable, a fast-growing fintech unicorn revolutionising credit and savings.
- Benefits: Flexible working, health coverage, office meals, and a vibrant team culture.
- Other info: Exciting career growth opportunities in a supportive and innovative environment.
- Why this job: Be part of a dynamic team making a real impact in the fintech space.
- Qualifications: Experience with SQL/Snowflake, strong Python skills, and a collaborative mindset.
The predicted salary is between 49500 - 60500 £ per year.
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
We'd love for you to become a key part of our Python Infrastructure team; a collaborative group that's always pushing the boundaries of what's possible. This role sits at the intersection of analytics engineering and Python-based data engineering. You’ll work on transforming and modelling data using SQL and dbt, while also leveraging Python to build data workflows, automate processes, and build tools to optimise day to day work.
No two days look the same here. We're building something great, and we're looking for the right people to grow with us. If that sounds like you, we can't wait to hear from you.
Our Tech Stack
You’ll work with a modern data stack centred around Snowflake, dbt and Python.
What we’re looking for
We’re looking for someone with strong technical fundamentals, excellent communication skills, and a genuine interest in building high-quality data products. More specifically, we’re looking for:
- Experience working with SQL/Snowflake or other modern data platforms
- Strong, modern Python development experience.
- Some experience building and maintaining data pipelines, ETL processes, or data-intensive backend services
- A collaborative working style and clear communication across technical and non-technical stakeholders.
- A keen desire to want to learn and input into a highly collaborative team
If you’ve worked in a cross functional environment, it would be a plus but not needed.
Interview process
- A quick phone call with one of the team
- A short coding exercise to complete in your own time
- Technical Video Interview for 60 mins
- Culture interview for 30mins
- Final Interview
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.
Data Engineer in London employer: Lendable
Lendable is an exceptional employer that champions innovation and flexibility, making it an ideal place for a Senior Kotlin/JVM Engineer to thrive. With a vibrant work culture that prioritises collaboration and personal growth, employees are encouraged to develop their skills while contributing to impactful financial products. The company's commitment to flexible working arrangements further enhances the work-life balance, making it a rewarding environment for those looking to make a difference in the fintech space.
StudySmarter Expert Advice🤫
We think this is how you could land Data 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 Lendable!
✨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 Data Engineer at Lendable.
✨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 Lendable.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Lendable, 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 Data 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 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.
