Senior Analytics Engineer

Relay Technologies
London - HybridPosted 27 March 2026

Job Description

Senior Analytics Engineer Relay is fundamentally reshaping how goods move in an online era. Backed by Europe’s largest-ever logistics Series A ($35M), led by deep-tech investors Plural (whose portfolio spans fusion energy and space exploration), Relay is scaling faster than 99.98% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen Relay’s Mission is to free commerce from friction. Today, high delivery costs act as a hidden tax on e-commerce, quietly shaping what can be sold online and limiting who can participate. We envision a world where more goods move more freely between more people, making the online shopping experience seamless and accessible to everyone. THE TEAM • ~110 people, more than half in engineering, product and data • 45+ advanced degrees across computer science, mathematics and operations research • Thousands of data points captured, calculated, analysed and predicted for every single parcel we handle • An intellectually vibrant culture of first‑principles thinking, tight feedback loops and relentless experimentation The Opportunity At Relay, we rely on data to guide how every parcel moves through our network — from when it enters the system to when it's delivered at the doorstep. Our data infrastructure is the backbone that powers everything from real-time operational decisions to strategic business insights to networks of autonomous AI agents. We're looking for a Senior Analytics Engineer to sit within our Last Mile squad; our biggest and most data rich squad. Your role will help contribute to the success of the key agentic workflows that power our Last Mile marketplace. You'll be joining at an exciting moment as we grow rapidly and expand our network across the UK. Who Will Thrive in this role? - Design core data models - Partner with engineers and business leaders within the Last Mile squad to design and build foundational data models that power analytics, data science and AI workflows - Build the foundations for our key AI systems - Our Last Mile marketplace is becoming increasingly agentic, you will be a key owner of the inputs that power these systems - Drive data quality - Implement testing, monitoring, and alerting to ensure our data is accurate, timely, and trustworthy - Collaborate - Work with team members across the business to understand their data needs and deliver solutions - Shape our practices — Help define and evolve our analytics engineering processes and standards as we scale What We're Looking For - 5+ years of experience as an analytics engineer, data engineer, data analyst or similar role - Extensive experience with SQL, particularly with BigQuery and PostgreSQL - Demonstrated experience with dbt, with a track record of building and maintaining efficient, scalable, and reliable DAGs - Python proficiency for data manipulation, scripting, and automation - Experience with data visualisation tools such as Tableau, Looker, or similar - Experience in effective communication, particularly in gathering requirements and guiding non-technical stakeholders to the right data solutions - Familiarity with using AI tools to accelerate your workflow Nice to Have: - Experience with orchestration tools like Dagster, Airflow, or similar - Experience building real-time or near-real-time data pipelines - Familiarity with machine learning workflows and feature engineering - Experience embedded in teams building customer facing products - Previous experience of learning and modelling an unfamiliar operational domain - A desire to see the real world impact of what you work on! Compensation, Benefits & Workplace - Generous equity, richer than 99% of European startups, with annual top-ups to share Relay’s success. - Private health & dental coverage, so comprehensive you’d need to be a partner at a Magic Circle law firm to match it. - 25 days of holidays - Enhanced parental leave. - Hardware of your choice. - Extensive per ... (truncated, view full listing at source)
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