Lead Data Engineer

Holborn and Covent Garden
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer (AWS & Snowflake)

Senor / Lead Data Engineer

Senior Data Engineer - Azure, BI & Data Strategy

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.

Products

Where to Advertise Data Engineering Jobs in the UK (2026 Guide)

Advertising data engineering jobs in the UK requires a different approach to most technical hiring. Data engineers occupy a distinct discipline that sits between software engineering, data science and cloud infrastructure — and the strongest candidates identify firmly with the data engineering community rather than with adjacent roles. General job boards consistently conflate data engineering with data analysis, data science and BI development, producing high application volumes but low candidate quality for specialist pipeline and platform roles. This guide, published by DataEngineeringJobs.co.uk, covers where to advertise data engineering roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Data Engineering Employers to Watch in 2026: UK and Global Companies Driving the Data Revolution

Data engineering is at the heart of the digital economy, transforming raw data into actionable insights, powering analytics, AI systems, and cloud infrastructure. As the UK and global markets continue to invest heavily in data platforms, pipelines, and real-time analytics, demand for skilled data engineers is growing rapidly. For professionals exploring opportunities on www.DataEngineeringJobs.co.uk , the critical question is: which companies are expanding, hiring, and shaping the future of data-driven business? This article highlights new data engineering employers to watch in 2026, including UK startups, scale-ups, and international firms expanding in the UK.

Careers

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

🍪 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.