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Analytics Engineer (UK Cards)

London · London, United Kingdom

Likely evergreen, first seen by us 1 day ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering & Product › Engineering › Cards UK Engineering — team source
Department: Engineering & Product › Engineering › Cards UK Engineering
From the employer’s posting

Before you apply

Work authorization
Must already have the right to workPlease note that unfortunately we're unable to sponsor for this position

What you’ll work on

Full posting

We're looking for an analytics engineer to contribute to the analytical foundation of the UK Cards team, a 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.

  • Build and improve data models for lending, pricing, portfolio and investor reporting

  • Help analysts turn requirements into robust data pipelines

  • Triage and resolve issues affecting the analytics pipeline and downstream data trust

  • Improve efficiency, reliability and cost of the transformation pipeline

  • Champion analytics engineering standards and culture

From the employer’s posting
We're looking for an analytics engineer to contribute to the analytical foundation of the UK Cards team, a 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.
Building and improving the data models that support lending decisions, pricing, portfolio analysis, and investor reporting.
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
contributing ideas to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time
Championing standards and contributing to the improvement of our analytics engineering culture.

About Lendable

Lendable is on a mission to build the world's best technology to help people get credit and save money.

In the employer’s words · Read in context · Company website ↗

Apply at Lendable

Posting record

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Likely evergreenReposted 3 times since Sep 2, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.

Status in our records
Live
First seen by us
Nov 2, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 3, 2026
Reposted
3 times since Sep 2, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 6 and day 47.

From 1,405 similar postings that came down. Coming down is not always a hire.

Lendable is hiring

9 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Analytics Engineer hiring is steady
  • Takes jobs down at a usual pace
  • 11% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • dbt
  • Fivetran
  • Snowflake
Where the posting names them
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. - Strong DBT and SQL is a must - Strong data modelling skills and a good understanding of how analytical datasets should be structured for reliability and usability.
- 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.
- 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.

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Applying through Ashby

  • No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.

Already applied? Track this application

Has Lendable posted this job before?

Yes. We’ve followed 2 other Analytics Engineer (UK Cards) jobs there since September 2026. 2 came down, usually after about 17 days.

  1. LondonCame down after 23 days, first seen Sep 28
  2. LondonCame down after 11 days, first seen Oct 21
  3. This jobUp 2 days so far, first seen Nov 2

About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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 most exciting unicorns with a team of over 800 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

  1. Take ownership: 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: Lendies are relentlessly resourceful. We challenge the status quo to solve problems and find smarter solutions

  3. Build the best technology in-house: we use 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 Cards team, a 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.

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.

  • Strong DBT and SQL is a must

  • 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

  1. 15 minute cognitive assessment

  2. Initial chat

  3. 30 minute chat with hiring manager

  4. 60 minute technical interview

  5. 60 minute culture interview

Please note that unfortunately we're unable to sponsor for this position

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.

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Pay

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Location & working pattern

London, United Kingdom

- 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
Work authorization

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