Data Engineer

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.