At a Glance
- Tasks: Own and improve data models for lending decisions and insights.
- Company: Join Lendable, a fast-growing fintech unicorn with a mission to revolutionise credit.
- Benefits: Flexible working, health coverage, office meals, and retirement savings plans.
- Other info: Collaborate with exceptional teams and enjoy social events beyond work.
- Why this job: Make a real impact in a dynamic environment with cutting-edge technology.
- Qualifications: Strong SQL skills and experience with ELT pipelines using dbt.
The predicted salary is between 60000 - 70000 £ 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
What you’ll be doing:
- Owning and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting
- Driving the development of our dbt models and transformation layer, working with analysts and stakeholders to improve the speed and quality of insight generation
- Helping define good modelling patterns, architecture, and implementation standards across the analytics engineering layer
- Supporting analysts at different technical levels, helping them build stronger engineering habits and become more effective with data
- Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to make sure data is generated, modelled, and used effectively
- Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time
- Scaling our data infrastructure to proactively support the requirements of a rapidly growing business
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:
Essential:
- Strong SQL skills
- Strong experience with ELT pipelines and transformation at scale, using dbt
- Excellent stakeholder management skills, with a proven ability to influence and negotiate with both technical and non-technical stakeholders
- Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability
- Good judgement in balancing longer-term platform improvements with day-to-day business needs
- The ability to spot inefficiencies in existing data workflows and improve them independently
- Comfort using AI tools effectively to move faster, improve quality, and strengthen day-to-day analytical and engineering workflows
Desirable:
- Experience with Snowflake or another modern cloud data warehouse
- An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns
- Fintech or scale-up experience
Interview process:
- Quick chat with a recruiter
- 15-minute cognitive assessment
- 60-minute technical interview (Interactive architecture/design exercise)
- 60-minute culture interview with primary stakeholders
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.
Senior Analytics Engineer (6 month FTC) employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analytics Engineer (6 month FTC)
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We think you need these skills to ace Senior Analytics Engineer (6 month FTC)
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Doist, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Doist, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Doist’s attention and show the tangible impact of your work.
How to prepare for a job interview at Doist
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Doist.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
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Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Doist.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Doist.
