Job Overview
Location
London
Job Type
Full-time
Category
Data Science
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Own and improve the data models that support lending decisions, pricing, portfolio analysis, and investor reporting for the US Loans team, Lendable’s fastest-growing business area.
- • Drive the development and maintenance of dbt models and the transformation layer to enhance the speed, quality, and reliability of insight generation across analytics teams.
- • Define and enforce good data modelling patterns, architecture standards, and implementation best practices across the analytics engineering layer to ensure scalability and maintainability.
- • Act as a bridge between analysts, backend engineers, product teams, and the data platform team to align data generation, modelling, and consumption with business needs.
- • Mentor analysts at varying technical levels to improve their engineering habits, data literacy, and effectiveness in working with structured analytical datasets.
- • Identify inefficiencies in existing data workflows and independently implement improvements to increase efficiency, reliability, and cost-effectiveness of the transformation pipeline.
- • Scale the data infrastructure proactively to meet the demands of a rapidly growing business operating in the UK and expanding into the US market.
- • Collaborate closely with stakeholders to translate business questions into reliable, reusable analytical models that reduce time-to-insight and improve decision-making.
- • Ensure high standards of data quality, lineage, and documentation across all analytical datasets used for critical business functions.
- • Leverage AI tools such as Claude to accelerate analytical workflows, enhance model quality, and automate repetitive tasks within the analytics engineering process.
- • Work within a modern data stack centred on SQL, Snowflake, dbt, Fivetran, and AI-assisted tools to build and maintain a robust, scalable analytical foundation.
- • Contribute to the strategic evolution of the analytics engineering function by balancing short-term business priorities with long-term platform improvements.
- • Support investor reporting requirements by ensuring data accuracy, consistency, and traceability in financial and operational metrics.
- • Participate in architectural design exercises and technical discussions to refine data models and improve the overall data ecosystem.
- • Promote a culture of data excellence by sharing knowledge, documenting patterns, and encouraging adoption of engineering best practices among non-engineering analysts.
- • Maintain a strong focus on usability and reliability of analytical datasets to empower non-technical teams to self-serve insights without dependency bottlenecks.
- • Work in a hybrid environment requiring three days per week in the London office, with opportunities for in-person connection through socials and off-sites.
🎯 Requirements
- • 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
🏖️ Benefits
- • Flexible working: hybrid model requiring three days in-office weekly, with opportunities for in-person connection through socials and off-sites
- • Private health cover for physical and mental wellbeing
- • Retirement & savings plans to support long-term financial wellbeing
- • Complimentary lunches prepared by in-house chefs on in-office days at select locations
- • Cycle-to-work and electric vehicle salary sacrifice schemes available in select locations
- • Employee referral programme with competitive bonus for successful referrals
Skills & Technologies
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About Lendable Ltd
Lendable is a UK-based fintech that operates an online consumer-lending platform using open-banking data and machine-learning underwriting to offer unsecured personal loans and car finance. Founded in 2014 and headquartered in London, it funds loans through an institutional peer-to-peer model, matching investors with borrowers seeking fast, fixed-rate credit. The company automates identity, affordability and risk assessment, providing near-instant decisions and same-day payouts while giving investors access to diversified consumer credit returns. Regulated by the Financial Conduct Authority, Lendable has originated more than ÂŁ2 billion in loans without maintaining physical branches, focusing on transparent pricing and mobile-first customer experience.
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