Data Engineer

Chelmsford
10 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer
I am working with a data driven Microsoft partnered consultancy who are looking for a Databricks Data Engineer to join their growing team. You will have the opportunity to work with some of the latest Microsoft technologies with a focus on projects on Databricks implementations.

You will join a team at the centre of a number of data-driven projects where you will be responsible for the design, development and creation of data solutions. You will work on the full end-to-end product lifecycle from platform design to insights creation.

As part of this role, you will be responsible for some of the following areas

Design, develop and maintain data pipelines that are responsible for the ingestion and transformation of data between different sources
Create and develop data models
Development of cloud data platforms solutionsTo be successful in the role you will have

Solid experience designing and delivering data solutions focused on Databricks
Strong ETL experience with tools such as ADF or SSIS
Experience working with Azure technologies - Synapse, Fabric, Data Lake
Knowledge of data architecture principles and data modellingIn this role you will be required to attend the office on an ad-hoc basis in London, with the remaining time spent working remotely. Some of the benefits included with the role are listed below

Starting salary of up to £60,000
Performance related annual bonus
25 days annual leave (plus bank holidays)
Employer pension contribution scheme
Private health/medical care
Various retail discounts and more!This is just a brief overview of the role. For the full information, simply apply to the role with your CV, and I will call you to discuss further. My client is looking to begin the interview process ASAP, so don't miss out, APPLY now! To do so please email me at (url removed) or call me on (phone number removed)

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 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.

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.