Data and AI Engineer

About Elio Elio is a data and strategic growth partner. We work with established businesses to surface the growth hiding in their data - building the data foundations first, then the insight, analytics, strategy and automation on top. We're profitable and growing fast. This is a chance to join a small, entrepreneurial team working in commercial, high-impact settings - where the work spans client delivery and helping build new products and ventures of our own. It's an early, mid-level hire: you'd work directly with the founder, shape how we deliver, and take real ownership of your projects. The role We're looking for a Data \& AI Engineer who is genuinely hands-on *and* comfortable taking projects from scoping to delivery. You'll build the data foundations our work rests on, turn messy client data into reliable analytics and insights, then help strategise and ship solutions that move the needle for clients. This isn't a pure-execution seat and it isn't a pure-management seat - it's both. You'll write the SQL and run the pipelines yourself, and also manage projects from a technical perspective, working alongside our other engineers. You won't own the commercial relationship (that sits with the commercial team) but you'll be trusted to represent your work in the room and speak confidently with clients and stakeholders. You'll also be close to how we build, helping shape the stack, the standards, and, over time, new products and ventures beyond client work. What you'll do * Design and build data foundations - pipelines, models and warehousing - that client work depends on. * Write clean, well-tested SQL / Python / JS and maintain good engineering practices (version control, documentation, reviews, CI). * Own the delivery of data projects - scoping, prioritising and keeping them on track - and speak to clients and stakeholders confidently about the work. * Turn data into insight: analytics, reporting and the groundwork for strategy and automation. * Build and integrate AI/ML-driven solutions where they genuinely add value. * Help shape how a growing, entrepreneurial consulting firm delivers - processes, standards, and the stack - and contribute to new products and ventures as they take shape. What we're looking for Must-haves * Passion for building software and problem solving. * Strong SQL and solid engineering fundamentals. * Comfortable with modern data platforms - e.g. Databricks, BigQuery or Snowflake. * Good software engineering discipline: Git/GitHub, branching, code review, clean commits. * Experience managing the delivery of data projects - scoping, prioritising and delivering to a client or stakeholder. * A self-starter who thrives in a small team, can own their work end to end, and is comfortable speaking with clients and stakeholders - translating technical work for non-technical people. Nice-to-haves * Cloud experience (Azure / GCP). * Understanding of wider engineering architecture e.g. having designed or deployed full-stack systems or side projects. * Hands-on with AI/ML or LLM-based tooling in production. * Exposure to marketing/growth data (ads, CRM, CDP, first-party data). * Consulting or agency background, or experience being the technical point of contact for clients. * A commercial, entrepreneurial streak - interest in how the work turns into products and outcomes. Why join * Entrepreneurial from day one: A key early hire in a small, profitable, founder-led team; you'll be close to the commercial side and to new products and ventures as we build them. * Ownership: Real say in how we deliver, plus a performance bonus and potential equity/options for the right person, so you share in what you help build. * Range: Real technical depth *and* project-delivery ownership, with direct exposure to clients - not siloed into one lane. * Impact: Your work is the foundation everything else is built on; you'll see it land. * Growth: Help define the stack, the standards, and the team as we scale. * Hybrid: Three days a week in central London with the team, the rest flexible. To apply Send your CV and a short note on a data project you owned end to end - what you built, the stack, and the outcome. A link to GitHub or relevant work is a plus. *We welcome applicants from all backgrounds.*