Data Engineer

Job Type:

Build a brilliant future with Hiscox
 

Hiscox is an international insurer specialising in luxury goods & property markets, as well as high-end professional insurance. As experts in risk, we empower individuals and businesses to achieve their ambitions. With offices in 9 European countries, we boast a highly international workforce, fostering a culture of inclusion, collaboration, and personal and professional growth.

The Europe Data Team is a cross-country, multidisciplinary group responsible for driving and enabling Hiscox Europe’s data capabilities. We combine expertise in Data Engineering, Data Analysis, and Data Management to deliver high-quality data pipelines, insightful reporting, and strong governance frameworks, working closely with business teams across Europe.

Our mission is to ensure trusted, consistent, and accessible data that empowers smarter decision-making and supports the evolution of our enterprise Hiscox Data Strategy.

The Data Engineer for the Europe Data Team designs, builds, and maintains the data pipelines and platform components that power our European analytics platform, which uses Microsoft Azure and Databricks.

Working with Data Analysts and the Data Product Manager, the Mid Data Engineer turns business requirements into reliable, well-tested data solutions, delivering new data requests, bug fixes, and improvements, and supporting the daily run of our production data processes.

With ongoing data transformation in Europe, this position offers strong exposure to a modern cloud data stack and the opportunity to grow technical depth and ownership, while supporting daily operations and existing commitments.

• Design and develop data pipelines on Databricks to ingest, transform, and deliver data;
• Integrate multiple data sources into a unified data platform;
• Contribute to data modelling and the optimisation of data structures;
• Support platform evolution aligned with cloud architecture (e.g., Azure / Databricks).

• Deliver new data requests, bug fixes, and improvements to existing processes within agreed priorities;
• Build and maintain business-facing pipelines and data products, from requirement through to production;
• Contribute to the migration of legacy processes to Databricks;
• Engage with business stakeholders where needed to clarify requirements.

• Ensure data quality, consistency, and performance of pipelines;
• Support the daily run of production batches, monitoring and troubleshooting issues to ensure timely resolution;
• Identify improvements in pipeline performance, cost, and reliability;
• Execute data deployments following defined processes, ensuring accuracy and smooth releases.

• Collaborate with Data Analysts and the Data Product Manager to deliver data solutions;
• Participate in peer code reviews and follow the engineering standards defined by the team;
• Document technical solutions and contribute to shared team knowledge;
• Contribute to the continuous improvement of data processes, standards, and platform evolution.

• Hands-on experience with Databricks is a must, including Spark/PySpark, Delta Lake, and job orchestration;
• Good understanding of data modelling (star schema) and ETL/ELT processes;
• Advanced experience with SQL for querying, transformation, and troubleshooting;
• Experience with Python for data engineering;
• Experience with Azure Data Factory or equivalent orchestration tooling;
• Familiarity with version control and deployment practices for data pipelines (e.g., Git, Azure DevOps).

• Ability to understand business needs and translate them into technical requirements;
• Strong communication skills, able to work effectively with analysts and business teams;
• Experience in Data Engineering or Data & Analytics roles (3+ years);
• Experience in analytics and reporting, ideally within the insurance industry.

• Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• Fluent in English, both spoken and written.

• Self-motivated and able to work independently while contributing effectively to a team;
• Positive attitude with a strong interest in creating value from data;
• Able to communicate ideas clearly to both technical and non-technical audiences;
• Skilled at translating business needs into practical technical solutions;
• Comfortable working in environments with ambiguity and change;
• Flexible, adaptable, and resilient.

Work with amazing people and be part of a unique culture