Platform Engineer

Our client running some of the most demanding data workloads in its sector is investing further in its analytics platform. The team is responsible for the systems that move, process and serve data for research and engineering, and they are looking for someone who enjoys building and operating distributed systems at scale

This role focuses on designing, operating and improving platforms that process high volume, high velocity data. The work involves close collaboration with researchers and engineers to make analytics reliable, scalable and easy to use, while ensuring performance and resilience keep pace with growth. The team values practical engineering, clear thinking and systems that work in the real world.

Responsibilities:

• Operating and evolving high throughput analytics platforms handling large volumes of data in production
• Running and improving systems built on modern data and streaming technologies, ensuring reliability, performance and scalability
• Automating platform operations using Python and infrastructure as code to reduce manual work and operational risk
• Working closely with research and engineering teams to enable experimentation safely and efficiently
• Improving reliability, performance and operational visibility across the data processing stack

What you will need:

• Strong experience running distributed data or analytics systems in production
• Comfort working with technologies such as Spark, Kafka, Trino, ClickHouse, Airflow or similar platforms
• Strong Linux fundamentals and the ability to write Python to automate operational workflows
• Experience working with Kubernetes and cloud platforms in production environments
• A mindset of ownership, curiosity and continuous improvement

For someone who enjoys building and operating core systems in a highly technical environment, this role is a good fit.