Lead Data Engineer

Working at CreateFuture CreateFuture is an AI-native consulting partner where people do work that matters and are supported to do it well. We work alongside organisations such as PayPal, adidas, NatWest, FanDuel and Money Saving Expert, building digital products and services that make a difference while always putting people first. We’re a team of creators. We write code, shape delivery, build go-to-market strategies, develop AI solutions and create the practices that support our people. We work side by side with our clients, challenging what’s not working and helping them to build the future. Our commitment to craft, quality, and culture has helped us scale to over 600 people in just a few years. CreateFuture is a Great Place to Work-Certified™ company and has won Best Workplaces UK multiple years in a row. Join us on our journey. Let’s create tomorrow, together, today. About the role and team: We are looking for a Lead Data Engineer to own the technical direction of a data engagement, working with Microsoft Fabric, Python, and PySpark across our data team. You'll lead a team of data engineers, setting the standards for how pipelines and architecture are designed, built, and operated, while remaining hands-on with the most complex technical challenges. You'll work closely with client stakeholders and CreateFuture's wider engineering capability to ensure delivery is both technically excellent and commercially sound. What you'll be doing: Own the technical direction of a data engagement, setting standards for pipeline architecture, data modelling, testing, and operational readiness Lead and technically direct a team of data engineers, allocating work, reviewing designs and code, and unblocking technical challenges Design and evolve data platform architecture on Microsoft Fabric, including data pipelines, Azure OneLake, and the broader Azure ecosystem Set and enforce CI/CD, testing, and operational practices across the engagement's data engineering workflows, using Azure DevOps Build professional relationships with key client stakeholders, translating business and data requirements into a coherent technical roadmap Troubleshoot and resolve the most complex issues in live data pipelines, and lead incident response when things go wrong We'd love to talk to you if you: Have extensive hands-on experience with a modern cloud data platform such as Microsoft Fabric (our current client's platform), Databricks, Snowflake, or Synapse, including designing production data platforms — the platform is the wrapper, not the skill, and strong engineering depth on one transfers readily to another Have deep SQL expertise and a strong grasp of data modelling and architecture (Kimball, data vault, medallion/lakehouse patterns, or domain modelling) — this is the clearest line between someone who operates a platform and someone who can design on top of it, and it's provider-agnostic Have strong proficiency in Python and PySpark for batch/ELT data processing at scale (this role centres on batch pipeline engineering — we treat streaming/real-time as a separate discipline and never assume the two are interchangeable) Have led or technically directed a team of data engineers, setting standards for pipeline design, testing, and delivery Have experience owning CI/CD and operational practices for data engineering workflows, ideally using Azure DevOps Are experienced working directly with client stakeholders, building trust and challenging where appropriate Have familiarity with the broader Azure ecosystem, including Azure OneLake and Azure ML, particularly for model industrialisation What we’ll offer you: We trust people to do their best work. That means flexibility over rigid rules, impact over activity, and real investment in your growth both professionally and personally. You’ll be part of a supportive, and friendly culture, surrounded by smart, curious people who care deeply about w