Data Engineering Manager / London / Microsoft Gold Partner

Opus Recruitment Solutions

City of London

10 months ago

Applications closed

Related Jobs

View all jobs

Business Intelligence and Database Lead

Data Scientist - London, UK (Fully REMOTE)

Celonis Data Engineer

Mid Level Data Engineer

Data Engineer

Data Analyst

Are you a passionate Data Engineering Manager ready to unlock the power of data? Our client is a leading UK-based consultancy seeking a skilled professional to shape data strategies, mentor dynamic teams, and deliver cutting-edge solutions. With hands-on expertise in Spark, SQL, and cloud platforms like Azure, you’ll lead end-to-end projects, drive innovation, and collaborate with clients across industries.

What You’ll Do:

Lead complex data engineering solutions with technical excellence.
Mentor teams and foster a culture of growth and quality.
Showcase your expertise in pre-sales and client workshops.
Design data pipelines, lakes, and warehouses with best practices.

Skills They're Looking For:

Proven Data Engineering experience (5+ years).
Consultancy experience is a must.
Leadership and multi-project environments experience.
Expertise in ETL, data modelling, and Azure Data Services.
Experience in designing and implementing data pipelines, data lakes, and data warehouses.
Hands-on experience with Apache Spark and bonus points for Microsoft Fabric
Any certifications are a bonus.

Benefits:

Competitive base salary
Hybrid work once a week into their Central London office
25 days holiday (plus bank)
Learning and Development budget towards certifications and exams
Life insurance
Private medical health insurance
And much more!

Ready to make an impact? Submit your CV showcasing your experience and UK work eligibility (no sponsorship available). We’re an equal opportunity employer celebrating diversity—join us! 🌟

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

Industry Insights

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

Apr 9, 2026

Products

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

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science 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.

Mar 24, 2026

Jobs

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.

Feb 10, 2026

Careers

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.