Analytics Engineer (Fintech)

TL;DR

Analytics Engineer (SQL/Snowflake/dbt): Building and optimizing the analytical foundation for the UK Motor team with an accent on data modelling and transformation pipelines. Focus on developing scalable datasets for lending decisions, improving data quality, and streamlining the transition from raw data to business insights.

Location: Hybrid in London. Must be based in the UK to attend the office Tuesday through Thursday.

Company

hirify.global is a profitable fintech unicorn building advanced technology to help people access credit and save money across the UK and US markets.

What you will do

• Develop and improve data models supporting lending decisions, pricing, portfolio analysis, and investor reporting.
• Build robust ELT pipelines and champion analytics engineering standards across the organization.
• Collaborate with analysts and product teams to translate business requirements into technical data structures.
• Triage and resolve pipeline issues to ensure data reliability and trust in downstream datasets.
• Optimize the transformation pipeline for increased efficiency, reliability, and cost-effectiveness.

Requirements

• Strong expertise in data modelling and structuring analytical datasets for usability and reliability.
• Proven experience with ELT pipelines and transformations at scale, specifically using dbt.
• Hands-on experience with Snowflake or a similar modern cloud data warehouse.
• Ability to communicate technical tradeoffs clearly to both technical and non-technical stakeholders.
• Proficiency in using AI tools to enhance engineering workflows and output quality.

Culture & Benefits

• Competitive compensation package including equity.
• Flexible hybrid work model with remote days every Monday and Friday.
• Fresh, healthy lunches prepared by in-house chefs provided Tuesday to Thursday.
• Comprehensive private health insurance coverage.
• Inclusive work environment in a fast-growing, high-scale fintech company.

Hiring process

• Initial screening call with an engineer.
• Short cognitive assessment.
• Technical interview (90 mins) including a team introduction and an interactive architecture/design exercise.
• Stakeholder interview (60 mins) focused on cultural fit, behavioral questions, and product mindset.