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# Lead Analytics Engineer

- **Company:** Harnham
- **Location:** London, United Kingdom (Remote available)
- **Experience:** Expert
- **Salary:** £70,000 - £90,000
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Data Analysis, Microsoft Azure, Python (Programming Language), Git, Streamlit Framework, Terraform, Docker
- **Published:** October 22, 2026
- **Apply:** https://www.reed.co.uk/jobs/lead-analytics-engineer/57483167

## About the Role

* Strong commercial experience delivering analytical products from concept through to business adoption.
 * Advanced Python development skills within analytics, data science, or decision-support environments.
 * Experience building reusable tools, frameworks, or data products used by multiple stakeholders.
 * Knowledge of technologies such as Python, Git, Azure DevOps, Docker, Terraform, Shiny for Python, Streamlit, Dash, R, or similar platforms.
 * Excellent stakeholder management and communication skills.
 * A consulting-style approach with the ability to work across varied business problems.
 * Experience operating in fast-moving environments with changing priorities.
 * Confidence working independently while collaborating effectively within distributed teams.

## Description

This is an opportunity to join a highly commercial analytics function where data products directly influence business decisions. Rather than sitting within a traditional IT team, you will work closely with senior stakeholders to solve complex challenges, build scalable analytical solutions, and create products that deliver long-term value across the organisation., You will:

 * Partner with senior stakeholders to translate complex business challenges into actionable analytical solutions.
 * Own the end-to-end delivery of analytical products, from initial discovery through to deployment and adoption.
 * Design and develop reusable frameworks, templates, libraries, and components that enable scalable delivery.
 * Build analytical tools and applications using Python and modern data product development practices.
 * Create solutions that are maintainable, configurable, and easily adopted by a wider team.
 * Collaborate with both technical and non-technical audiences, communicating insights clearly and effectively.
 * Contribute to development standards, governance processes, and best practices.
 * Support and mentor colleagues through knowledge sharing, peer reviews, and technical guidance., * The opportunity to work closely with senior decision-makers and influence business strategy.
 * Exposure to a broad range of analytical challenges and high-impact projects.
 * Clear opportunities to shape team standards, frameworks, and ways of working.
 * Ongoing professional development and career progression within a growing analytics function.