Data Engineer

Tired of keeping pipelines alive? Move into a role where you own the architecture.

The customers are in Defence, Government and National Security, and the datasets are big, messy and multi-source.

You’ll work closely with data scientists, software engineers and architects, and directly with the client, so you always know what the platform is for.

What you’ll be working on

• Data platforms and pipelines, batch and streaming, built for scale
• Data lakes and cloud-native architecture on AWS or Azure
• Ingesting and integrating data from lots of different sources
• Data foundations for analytics, AI and ML workloads
• DevSecOps and Infrastructure as Code
• Python, SQL, Spark, Docker, Kubernetes and CI/CD

Why it’s worth a look

• Real influence over how platforms get designed and built
• Close to the customer and the decision-makers
• Exposure to AI/ML workloads, not just moving data from A to B

Must have: commercial data engineering experience, strong Python and SQL, hands-on Spark, and cloud-native platform experience on AWS or Azure. Comfortable with Docker, Kubernetes and CI/CD.

Nice to have: data modelling and metadata management, AI/ML pipelines and feature engineering.