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# Senior Analytics Engineer (6 month FTC)

- **Company:** Doist
- **Location:** Greater London, UK (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Data Analysis, Data Infrastructure, Data Warehousing, Database Queries, Snowflake, Backend, Data Pipelines
- **Published:** September 8, 2026
- **Apply:** https://www.collegerecruiter.com/job/2840674028-senior-analytics-engineer-6-month-ftc

## About the Role

* 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

Desirable:

 * Experience with Snowflake or another modern cloud data warehouse
 * An interest in helping analysts raise their technical bar through support, mentoring, and better shared patterns
 * Fintech or scale-up experience

## Description

* 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 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
 * Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time
 * Scaling our data infrastructure to proactively support the requirements of a rapidly growing business


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