Data Engineer

Hertford
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer - AI Analytics and EdTech Developments

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer
Based in Cheshunt, Hertfordshire
Permanent, full-time, 37 hours per week
Salary: £54,835 - £60,927 per annum

Reliable data is at the heart of good decision-making. We’re looking for an experienced Data Engineer to join our newly established data team and work with them to deliver reliable, high-quality data that supports informed decision-making and enables us to deliver better outcomes for our customers.

In this role, you’ll design and maintain scalable data pipelines and robust data models, helping to ensure our data is accurate, accessible, and secure. You’ll also improve troubleshooting by introducing error handling and logging and optimise efficiency by monitoring data performance and applying fine tuning techniques. Writing complex queries (SQL, Python and Spark), documenting data structures and working with colleagues to respond to business needs while ensuring alignment with governance standards and GDPR are also key in this role.

 We’re looking for someone with…

  • Proven experience in data engineering or data platform development.
  • Experience with testing frameworks and writing test plans for data pipelines.
  • Strong analytical and problem-solving skills.
  • Strong SQL skills and experience with query optimisation.
  • Knowledge of Microsoft Fabric (Lakehouse, Dataflows, ADF).
  • An understanding of data modelling concepts (e.g. dimensional, star schema, denormalisation)
  • Knowledge of performance tuning techniques for ETL and SQL processes
  • Familiarity with data governance principles and GDPR

    Due to the type of data you’ll have access to in this role, you’ll be required to undertake a basic criminal record (DBS) check.

    We’re a social business, based in Cheshunt and across southeast Hertfordshire, helping local people by renting or selling affordable homes. We offer services designed to help our customers live comfortably in their homes, and we work to keep our buildings and estates maintained, offering support when money becomes an issue or when people get older. Our mission is to make a sustainable, positive change to the housing crisis for our customers and communities.

    We enjoy a benefits package that offers something for everyone, including…

  • 27 days’ holiday plus bank holidays (pro rata for part-time colleagues).
  • Buy and sell holiday scheme.
  • Cross-organisational bonus scheme.
  • Up to 12% pension contribution.
  • Life assurance (three times salary).
  • Funded health cash plan or subsidised private medical insurance.
  • Range of special and family leave.
  • Car loans, cycle to work and electric car lease scheme.
  • Discount vouchers and more.

    The closing date for this vacancy is 2nd February 2026.

    We are a Disability Confident employer, which means that we offer an interview to a fair and proportionate number of disabled applicants who meet the minimum selection criteria for the job.

    Other organisations may call this role ETL Engineer, Data Pipeline Engineer, Analytics Engineer, Data Platform Engineer, or BI Developer.

    We’re committed to building an inclusive workplace where equity, diversity and inclusion are part of our culture, as we recognise the benefits of a diverse workforce. Our 3-year EDI strategy outlines how we’ll achieve this. We strongly welcome applications from underrepresented groups and groups which are identified as a priority within our strategy, including LGBTQIA+, Black, Asian and Minority Ethnic communities, applicants with disabilities and people under 30.

    We understand that some candidates, particularly from certain groups, may hesitate to apply unless they meet every requirement. While we’re looking for people with the right skills and experience, we also value diverse backgrounds and transferable skills. If you meet most of the criteria and believe you’d thrive in the role, we encourage you to apply.

    All our vacancies are open to flexible working arrangements, something we are really proud of. The extent to which flexible working is possible will vary between jobs according to the needs of the business and our customers.

    So, if you’re ready to take your next step as a Data Engineer, please apply via the button shown. This vacancy is being advertised by Webrecruit. The services advertised by Webrecruit are those of an Employment Agency

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.

Careers

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

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.

Jobs

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

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.

Education

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

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.