We are seeking a Data Engineer to join our Data & Analytics team, responsible for building and maintaining scalable data pipelines, data models, and cloud-based infrastructure that powers data and analytics across the organisation.  YOUR CHALLENGE: * Design and develop data pipelines using Python (PySpark), applying best practices for performance and reliability.  * Ingest and integrate (real-time, batch) diverse data sources into the data lake, ensuring data quality and accuracy.  * Maintain data models and the overall data estate codebase.  * Daily monitoring and operations on cloud data platforms (primarily Azure / Microsoft Fabric).  * Monitor data processes, pipelines, troubleshoot issues, and support daily data operations.  * Collaborate with engineers, analysts, and business stakeholders; support ad hoc data analysis requests.  * Drive continuous improvement through training and self-development.  * Any other ad hoc tasks that may be required by the business from time to time.   TO DO IT, YOU WILL NEED: * A Degree in IT, Computer Science, or related fields.  * Proven experience as a Data Engineer including designing and building scalable ETL processes for batch and real-time data lakes / warehouses.  * Hands-on experience with cloud data services. Microsoft Synapse and Fabric experience is a plus.  * Strong SQL skills; experience with relational databases and complex queries.  * Proficiency with compute tools such as Databricks or Jupyter.  * Experience orchestrating pipelines using ADF, Fabric Pipeline, Airflow, AWS Step Functions, or similar.  * Coding proficiency in PySpark, Python, Scala, or equivalent languages.  * Experience with CI/CD tooling: Git, Azure DevOps, Jenkins or equivalent.  * Familiarity with distributed systems (Kafka, Spark, Hive, Hadoop) and BI tools (such as Power BI) is an asset.  * Comfortable delivering in a fast-paced, agile environment.  * Strong analytical and problem-solving skills.  * Excellent communication and team collaboration.  * Self-motivated with a drive for continuous learning.