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.

Data Engineer

Job Description