Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Data Engineer

Holborn and Covent Garden
7 months ago
Applications closed

Related Jobs

View all jobs

Lead Data engineer

Lead Data Engineer - Microsoft Fabric - Hybrid - £75k

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer - Preston

Lead Data Engineer ( Databricks )
London - Hybrid - Remote
Permanent
£100,000 - £130,000 plus up to 20% bonus based on performance and commercial contribution

About the Role

We’re looking for a Lead Data Engineer to spearhead some of our clients most strategic Databricks engagements.

This is a senior client-facing leadership role, blending hands-on technical delivery with architectural design and pre-sales influence.

You'll be leading high-performing squads, guiding complex transformations, and working directly with senior stakeholders to bridge business needs and engineering excellence — particularly in industries like manufacturing, utilities, and aviation.

This is a key hire to support our clients expanding Databricks practice, to build capacity for future growth.

What You’ll Be Doing

  • Act as the technical lead on client engagements, owning design and delivery of data solutions in Databricks.

  • Architect robust, scalable data platforms using the medallion architecture.

  • Translate business requirements into scalable workflows, advising on data governance, quality, and security.

  • Design and implement complex data pipelines using tools like Delta Live Tables (DLT) and Unity Catalog.

  • Guide teams in implementing best practices across engineering, DevOps, and model deployment.

  • Support pre-sales activity, including shaping proposals, estimates, and technical roadmaps.

  • Provide technical leadership, mentorship, and oversight to squads of Senior and Associate Engineers.

  • Collaborate closely with Platform Engineers and Platform Architects to align infrastructure with data needs.

  • Contribute to growing the Databricks capability – from delivery frameworks to internal tooling and capability development.

  • Lead a team of data engineers, fostering a collaborative and growth-oriented environment.

  • Evaluate new data engineering technologies and strategies, assessing their relevance and fit for the organisation’s strategic goals.

  • Work closely with the commercial team to scope projects and develop proposals that align technical capabilities with client requirements.

    Essential Skills & Experience

  • 8+ years in data engineering, with at least 2+ in a technical leadership role

  • Proven experience designing and leading Databricks-based data platforms

  • Deep understanding of the medallion architecture, data lakehouse design, and transformation workflows

  • Hands-on expertise with DLT, Unity Catalog, and model deployment frameworks

  • Strong communication and consulting skills – able to lead client conversations and manage stakeholders

  • Experience in agile delivery environments and cross-functional teams

  • Commercial awareness – comfortable contributing to pre-sales, growing accounts, and engaging with commercial targets

    Desirable Skills

  • Experience in physical asset-heavy industries (e.g. utilities, manufacturing, aviation)

  • Familiarity with platform and DevOps collaboration, especially on AWS or Azure

  • Certifications in Databricks or cloud platforms (AWS/Azure)

  • Background in consulting or client delivery environments

    Why Join?

  • Join a consultancy that’s doubling down on Databricks with enterprise-grade delivery

  • Be the go-to technical leader on projects with real-world business impact

  • Shape the future of our Databricks workforce strategy and delivery model

  • Career progression into Delivery Lead, Practice Lead, or Pre-Sales Specialist

  • Competitive compensation and strong bonus structure, aligned with delivery and commercial impact

    To find out more about this high profile Lead Data Engineering position, click apply

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.