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.
Key Responsibilities
Pipeline Development & Integration
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).
Delivery & Business Support
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.
Quality & Operations
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.
Collaboration & Solution Design
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.
Skills
Technical Skills
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).
Functional Skills
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.
Education & Languages
Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, or a related field;
Fluent in English, both spoken and written.
Person Specification
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.
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