Data Engineer - AI Analytics and EdTech Developments
Job reference REQ000296 Date posted 10/02/2026 Application closing date 08/03/2026 Location Berkhamsted Salary Competitive Package Benefits detailed in Applicant Information Pack Contractual hours Blank Job category/type Non-Teaching Data Engineer - AI Analytics and EdTech Developments Job description Berkhamsted Schools Group is seeking a skilled Data Engineer (AI & Predictive Analytics) to help advance our digital, data, and AI capabilities. This...
Berkhamsted Schools Group
Berkhamsted
Data Engineer (AWS)
Data Engineer (AWS) Location: Telford / Worthing Base Locations (Hybrid 2-3 days onsite) Salary: £50,000 - £60,000 + Bens, Perks, Healthcare Options, Unlimited Training Budget Security Clearance: Must be eligible for SC Clearance (5+ years UK residency) Sector: Public Sector & Government Client Build the Data Infrastructure That Powers the Public Sector We are looking for experienced Data Engineers to...
83zero Ltd
Telford
Cloud Database Administrator
Cloud Database Administrator / Leeds (1-2x per month in the office) / £55,000 - £65,000 About the Role We're seeking a Cloud Database Administrator to help safeguard and evolve a large, AWS-hosted database estate supporting critical business systems in a regulated environment. This is a hands-on role combining strong SQL fundamentals with practical experience operating databases in the cloud. You'll...
Corecom Consulting
Leeds
SAS Data Engineer
SAS Data Engineer Salary: Up to £60,000 + Benefits Location: UK (Public Sector Programme) Security Clearance: SC Eligibility Required We are currently seeking an experienced SAS Data Engineer to join a long-term public sector programme focused on modernising data platforms and delivering secure, reliable data solutions at scale. This is an excellent opportunity to work on meaningful projects that support...
83zero Ltd
Telford
Lead Data Engineer
Lead Data Engineer Salary: £75K - £85K Location: Manchester hybrid Data Idols are working with a data-driven organisation that is expanding its cloud data engineering capability and is looking for a Lead Data Engineer to join the team. This role sits within a modern data engineering function and focuses on designing robust, scalable architectures for data ingestion and analytics, with...
Data Idols
Manchester
Azure Data Engineer
Azure Data Engineer | £(Apply online only) per day | Bristol | Hybrid | 6‑Month Initial Term | A large‑scale data transformation programme is underway, and our client is looking for an experienced Azure Data Engineer to support the rebuild of their cloud data platform. This role is hands‑on and delivery‑focused — you’ll be designing and developing Azure‑native data pipelines,...
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.
If you’re applying for data engineering jobs in the UK, the first thing to understand is this:
Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look.
In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.
Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale.
Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply.
Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles.
The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work.
This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.
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Job Seekers:
Explore a wide range of data engineering roles, from building and maintaining data pipelines to designing and implementing data warehouses and data lakes. Find your next challenge in big data processing, cloud data platforms, and data integration.
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