Analytics Engineer

hackajob is collaborating with Lendable to connect them with exceptional professionals for this role.

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.

• 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'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 work with data, and support the team in keeping our warehouse a reliable, strategic asset for the business.

• 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.

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

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.

• 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

• 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
• P…