Data Engineer - Databricks - £60,000

London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer - AI Analytics and EdTech Developments

Data Engineer - (Python, SQL, Machine Learning) - Robotics

Data Engineering & Data Science Consultant

Data Engineering & Data Science Consultant

MLOps Data Engineer (GCP)

MLOps Data Engineer (GCP)

Data Engineer - Databricks - £60,000 - Hybrid

Company Overview:

Our client is a growing data-focused consultancy partnered with both Microsoft and Databricks they excel in delivering exceptional data solutions to a diverse array of clients. Their expertise includes advanced data analytics, artificial intelligence, and custom finance solutions, ensuring tailored support for each unique business need. Recognising the importance of work-life balance, the company fosters a culture that values employee well-being, significantly boosting morale and productivity. Consequently, the role offers a lot of flexibility when it comes to working patterns.

Client has been growing massively, this is a great opportunity for professional development working with top engineers on cutting-edge tech.

Role Overview:

The client is looking for a talented Data engineer to come in as a consultant to work on a large variety of projects across multiple industries. The role will utilise some really interesting tech, with a key focus on the full capabilities of Databricks and additional technologies such as Microsoft Fabric.

As a consultant you will be working directly with clients to understand business needs and implement industry best data solutions accordingly.

Requirements:

Strong Databricks experience
Strong Python and SQL Skills
Azure, or AWS, experienceBenefits:

Bonus
Flexible Working
25 Days Annual Leave + Bank Holidays
Annual Salary Review

  • Much more

    This is an unmissable chance to hone your skills and grow your career working for a top Microsoft partner, interviews are already underway so don't miss your chance. Apply Now!

    Contact - (url removed) // (phone number removed)

    Azure Databricks,Data Engineering, Databricks, ADF, Data Factory, synapse, Data Engineer, Data Consultant, Consultancy, Microsoft, ETL, Kafka

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.