Junior Data Engineer

Aegon UK
Edinburgh
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer - £62,000 - Hybrid

Data Analyst / Junior Data Scientist

Junior Data Analyst

Senior Data Engineer

Lead Data Engineer

Senior Data Engineer - Azure, BI & Data Strategy

Junior Data Engineer


Type: Permanent


Location: Edinburgh (We believe in the power of in-person collaboration, and our hybrid model requires colleagues to be in the office a minimum of 40% of their time)


Salary: A competitive salary from £27,760 - £34,700 depending on experience


Closing date: 24 August 2025


Our purpose is to help people live their best lives - and that includes our colleagues. We invest in your talents to help you grow professionally and personally.


About us: We support people with their pensions, savings, and investments. At Aegon, we strive to create a diverse organization that promotes equity, inclusion, and belonging.


Role overview: As a Junior Data Engineer, you will join a team of high-quality professionals and get involved in real projects from day one. Your responsibilities will include data development tasks such as assessing data quality, reviewing requirements, building data pipelines, reporting, and contributing to technical delivery for Finance teams.


In addition, you will collaborate with cross-functional teams to identify and implement data solutions that add business value. You will be involved in designing and architecting scalable, reliable, and secure data systems, as well as optimizing data workflows and automating processes to improve efficiency and accuracy.


Key Responsibilities:



  1. Develop, maintain, and optimize data pipelines using SQL, Python, DataStage, and Cognos.
  2. Ensure data integrity and quality across various data systems.
  3. Collaborate with teams to understand data requirements and deliver solutions.
  4. Implement and maintain data architecture to support business needs.
  5. Analyze and interpret complex data sets to provide insights.


Qualifications:



  • Bachelor's degree in computer science, Information Technology, or related field.
  • Proficiency in SQL, Python, DataStage, and Cognos.
  • Knowledge of data and systems architecture.
  • Excellent analytical and problem-solving skills.
  • Ability to work independently and as part of a team.
  • Strong communication and interpersonal skills.
  • Strong organizational skills and the ability to manage multiple tasks.
  • Adaptability and willingness to learn new technologies.


Benefits:



  • Enhanced pension scheme from November 2025: 7% employee contribution topped up by an additional 13% if you contribute 7%.
  • Discretionary bonus based on performance.
  • 34 days of leave per year (including bank holidays, pro-rated for part-time).
  • Private medical cover, life assurance, critical illness cover, parental leave, and various lifestyle benefits such as retail discounts, cycle2work scheme, subsidized restaurant, and online GP appointments.


To learn more about working at Aegon, click here.


Application note: Please confirm you have the right to work in the UK. Successful candidates will undergo checks including credit, criminal record, and reference checks before starting.


#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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.