Lead Data Engineer - Databricks

ARCA Resourcing Ltd
London
2 weeks ago
Create job alert

Lead Data Engineer - Databricks

Location: Remote UK or hybrid / onsite at one of our clients’ offices

Working Pattern: Remote UK / Hybrid or office based

Salary: Competitive

ARCA Resourcing is proud to be partnered with an innovative and leading retailer that is investing heavily in its data capabilities to drive smarter decision-making across the business. As part of this transformation, we’re looking for a Lead Data Engineer to play a key role in shaping and delivering the organisation’s modern Enterprise Data Platform.

This is an opportunity to combine hands-on engineering with technical leadership, working with cutting-edge technologies while mentoring engineers and influencing the direction of a high-impact data platform.

The Opportunity

The organisation operates a modern data stack built around a Databricks-based lakehouse architecture, alongside a Customer Data Platform (CDP), enterprise analytics tooling, and self-service reporting capabilities.

As a Lead Data Engineer, you will oversee multiple delivery squads, ensuring consistent engineering standards and guiding the design and delivery of scalable data solutions. You’ll coordinate technical delivery across teams while remaining hands-on with architecture, pipelines, and best practice development.

This role is ideal for someone who en...

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data/Head of Data Engineer

Lead Data Engineer (AWS & Snowflake)

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.