Analytics Engineer

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.

1. 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

2. Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo

3. Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting

As an Analytics Engineer, you’ll own the data models and transformations that underpin credit decisioning, pricing, portfolio performance, and investor reporting for our UK and US businesses.

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 operate with a high degree of ownership, helping shape the modelling layer, improving how analysts work with data, and ensuring our warehouse remains a strategic asset for the business.

• 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 and mentoring 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.

• Leading triage and resolution of issues that affect the analytics pipeline or reduce trust in downstream datasets.

• Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.

You’ll work with a modern analytics stack centred around Snowflake, dbt, and Fivetran.

We’re looking for someone with strong analytics engineering fundamentals and the ability to apply them pragmatically in a fast-moving environment.

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.

• 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.

• 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.

• An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns.

• Initial call

• 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

• 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.

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