Principal Data Engineer

Aegon
Witham
2 weeks ago
Applications closed

Related Jobs

View all jobs

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Description

Principal Data Engineer

Permanent

Location: Edinburgh or Witham(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£57,600 - £86,400,depending on the experience you can bring 

Closing date: 30th May 2025

We’re a company of ambitious, collaborative problem-solvers who get things done – we’re looking for like-minded people to join us.

We help people live their best lives.We help them with the big stuff, for the moments that matter: Pensions, Savings, Investments. At Aegon, we strive in creating a diverse organisation that plays a meaningful role in driving greater equity, inclusion and belonging.

Data is crucial to our organisation — it shapes how we operate every day and is fundamental to achieving our goals. As we continue to evolve, our data function is undergoing a transformation. We're reimagining how we work, incrementally improving our data architecture, strengthening our engineering practices, expanding our capabilities, and driving innovation across the business.

We are hiring for multiple Principal Data Engineers in Edinburgh or Witham. In this role, you will lead the design and development of complex cloud-first data solutions in AWS, ensuring high-quality, scalable code and engineering excellence. You will collaborate with data engineers, product managers, analysts, BI engineers, and data users to deliver innovative, self-service data solutions. You’ll also work with senior stakeholders to shape the roadmap and backlog for the data capability team, aligning with strategic business objectives. Your responsibilities will span the entire data lifecycle, from design to production — ensuring solutions meet defined standards.

Key Responsibilities:

Team Leadership: Provide technical guidance, foster continuous learning, and take ownership of team capabilities and deliverables.Architect and Build Scalable Data Solutions: Design and develop scalable data solutions using AWS-native technologies (DMS, Glue, RDS, Lambda, Python, PySpark, Athena, DynamoDB, PostgreSQL, Kinesis, SQS, SNS) and BI tools (Tableau, Power BI, QuickSight).Cross-Functional Collaboration: Working closely with cross-functional teams to gather business requirements, designing effective data solutions, and ensuring timely and high-quality project delivery.Champion Engineering Best Practices: Establish coding standards, conduct code reviews, and promote quality assurance practices.Ensuring Data Quality and Reliability: Develop and maintain automated testing frameworks for data pipelines.Platform Design: Architect data platform solutions aligned with AUK Architecture team standards.

We’d love to hear from you if you have:

Experience in a Senior, Lead, or Principal Data Engineer role. Strong track record of delivering cloud-based data platforms, data lakes, BI, and advanced analytics solutions. Deep understanding of data architecture principles and data modelling techniques in modern serverless cloud environments. Hands-on experience with Python, PySpark, SQL, and infrastructure-as-code tools (AWS CloudFormation, Terraform, AWS CLI). Extensive expertise in AWS services and architecture, including EC2, S3, DMS, Lambda, API Gateway, AWS Glue, and QuickSight or similar in other Cloud environments like GCP / Azure. Proficiency in building scalable, serverless data pipelines using cloud-native ETL tools, such as AWS Glue, Azure Data Factory, or Google Dataflow. Experience with SQL and NoSQL cloud databases. Strong grasp of data engineering principles and best practices. Ability to implement robust data quality controls and monitoring frameworks. Knowledge of data security best practices. Proven ability to lead and mentor engineering teams. Skilled in translating business requirements into technical specifications.

What’s in it for you?

A non-contributory pension between 8%-12% A discretionary bonus, depending on personal and company performance 36 days leave per year (including bank holidays, pro-rated for part-time)

We also offer private medical cover, life assurance, critical illness cover, enhanced parental leave and a variety of lifestyle benefits to help our employees live their best lives, including retail discount vouchers, cycle2work scheme, subsidised restaurant and online GP appointments. To find out more about what to expect at Aegon .

We're looking for talented individuals who are ready to make a real impact. If you're excited about new challenges and want to work with a team that values your skills, apply today!

The legal bits

We’ll need you to confirm you have the right to work in the UK. If we offer you a job and you accept, there are some checks we need to complete before you can start with us. This will include a credit and criminal record check, as well as providing satisfactory references.

Equal Opportunity Employer:

We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless of their age, disability, race, religion/belief, gender, sexual orientation or gender identity.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.