Senior Data Engineer

Senior Data Engineer (Databricks / Spark / Azure)

Job description:

• 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

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.

• 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
• Fluent English

The following are nice to have:

• 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