Data Engineer

The Acorn Group
Liverpool
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

Posted Thursday 20 November 2025 at 01:00


We are seeking a talented and experienced Data Engineer to join our innovative and collaborative Database and AI Team. In this role, you will play a key part in shaping our data strategy and driving business success. Your skills will contribute directly to our forward‑thinking initiatives. At Acorn we value and prioritise innovation, teamwork, and continuous development.


Key part of this role is to support our strategic data goals, ensuring system resilience and performance, and building secure, scalable database architectures.


Job Title: Database Engineer


Location: Liverpool City Centre on a hybrid working basis


Working hours: 37.5 hours per week, Monday to Friday, 9am to 5:30pm


What you will be doing

  • Design and implement robust data ingestion pipelines for unstructured data using modern data engineering tools and frameworks.
  • Develop and maintain scalable storage solutions (e.g., data lakes, NoSQL databases) optimized for unstructured data.
  • Collaborate with data scientists, analysts, and software engineers to ensure data availability, quality, and usability.
  • Apply data parsing, extraction, and transformation techniques (e.g., NLP, OCR, image/audio processing).
  • Implement data governance, metadata management, and data cataloging for unstructured data assets.
  • Monitor and optimize data workflows for performance, reliability, and cost‑efficiency.
  • Ensure compliance with data privacy and security standards.
  • Share knowledge and mentor team members
  • Stay ahead of the curve with the latest database technologies
  • Experience of real‑time cloud streaming solutions

What we are looking for

  • Experience dealing with unstructured data including voice, chat, image
  • Proven ability to manage secure, high‑performance database environments
  • Excellent communication and cross‑functional collaboration skills
  • A passion for continuous learning and innovation
  • Confluent/Apache Flink knowledge

Grow with Acorn

At Acorn Insurance, we’re proud of our Liverpool roots — and even prouder of how far we’ve come. As part of the Acorn Group, we bring over 40 years of specialist insurance expertise to the table. From humble beginnings, we’ve grown into a national leader, now employing 1,700+ people across the UK and reached a milestone £750 million in total value of insurance policies written in 2024.


We’re growing fast, with new opportunities emerging every week. That growth is largely due to the values we share:



  • 🦏 We run through walls for our customers and each other
  • 🐐 We challenge the status quo
  • 🐧 We succeed when we help those around us succeed
  • 🐆 We decide quickly when the smart thing to do is use our judgement
  • 🌴 35 days’ holiday (including bank holidays) with additional buy/sell options
  • 🧠 24/7 mental health support & free counselling available
  • ☝ Grow with us:Through career fairs, leadership programs, and learning on the go!
  • 💸 Flexible benefits, including early access to salary via our internal platform
  • 🏡 Hybrid working options to support work‑life balance and individual needs

Our Commitment to our colleague’s

These aren’t just words — they’re the principles we live by. And we’re proud to back them up with real action, earning recognition and accreditation from leading organisations that share our commitment to people and growth:



  • 🧠 Mindful Employer– championing mental health and wellbeing
  • Disability Confident Level 1 & 2– creating accessible, inclusive opportunities
  • 🌸 Menopause Friendly accredited– supporting every stage of life
  • 🎖️ Armed Forces Covenant signatory– honouring those who serve
  • 🏆 Great Places to Work 2024/25– fostering an engaging and positive workplace culture
  • 📈 Best Place to Work for Development– proud to be investing in people’s future
  • 👩💼 Best Place to Work for Women– breaking down barriers to women's career progression

If you’re looking for a company with a strong culture, real career progression, and a people‑first approach — all rooted in the heart of Liverpool — Grow with Acorn.


A Few Things to Know Before You Apply

We’re really excited that you’re considering joining Acorn! To help everything go smoothly, here are a couple of things to keep in mind:


🔍 Checks & Clearances
All roles at Acorn are subject to DBS and financial checks. Any offer we make will be conditional until these are completed to a satisfactory standard.


🌍 Visa Requirements
Because our training is quite comprehensive, we can only consider applicants who have at least one year remaining on their Graduate or Post‑Study Work visa. At the moment, we’re not able to offer visa sponsorship.


💬 We’re Here to Support You
We’re committed to creating an inclusive, supportive workplace where everyone can flourish. If you need any adjustments during the recruitment process—or once you’re part of the team—just let us know. Whether it’s flexible hours, adapted equipment, or a bit of extra support, we’ll work with you to make sure you can do your best work.


#J-18808-Ljbffr

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 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.

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.

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.