Senior Data Engineer; Databricks​/Spark​/Azure

This is a hands‑on engineering role suited to a senior professional who enjoys owning complex technical features from concept through to production and who thrives in large‑scale, cloud‑based data environments.

As a Senior Data Engineer, you will play a key role in the evolution of a strategic enterprise data platform. You will take ownership of complex technical initiatives, collaborating with engineers, architects, and business stakeholders to deliver robust, scalable, and high‑performing solutions.

You will be involved throughout the full software development lifecycle, from requirements gathering and solution design to implementation, testing, deployment, and operational handover.

• Design, develop and implement scalable data platform solutions
• Own technical features end‑to‑end, ensuring successful delivery into production
• Build and optimise large‑scale data processing pipelines and workloads
• Troubleshoot performance, scalability and reliability challenges
• Contribute to architecture and technical design discussions
• Collaborate with engineering teams and stakeholders to manage dependencies and align delivery plans
• Drive engineering best practices including code reviews, testing, documentation and operational readiness
• Proactively identify risks, bottlenecks and improvement opportunities across the platform

• 5+ years of experience as a Data Engineer, Software Engineer, Platform Engineer or similar
• Strong experience with Databricks
  , Apache Spark and Python
• Solid understanding of distributed computing and large‑scale data processing concepts
• Experience working within cloud‑based environments, ideally Microsoft Azure
• Proven track record of delivering production‑grade solutions in complex environments
• Strong understanding of scalability, performance optimisation, reliability and maintainability
• Experience working in Agile engineering teams
• Excellent communication and stakeholder management skills

• Experience with in financial services, insurance or other highly regulated industries
• Exposure to technologies such as Kafka, Flink, Snowflake, Big Query or similar modern data platforms
• Experience supporting platform engineering or data platform initiatives