Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Principal Data Engineer

Aegon
Edinburgh
1 month 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

Social network you want to login/join with:

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 £63,440 - £95,160,depending on the experience you can bring

Closing date: 21st July 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, sexualorientationor gender identity.


#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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.