Responsibilities: Build and optimise scalable data pipelines using PySpark and SQL Design and implement ETL/ELT processes for batch and streaming data Develop data solutions using Databricks Lakehouse and Delta Lake Ingest and integrate data from internal and external sources (e.g. Kafka, CDC) Optimise Spark jobs and data workflows for performance, scalability, and cost efficiency Manage infrastructure and environments using Terraform (IaC) Ensure data quality, monitoring, and reliability Implement governance and access controls (e.g. Unity Catalog) Deliver clean, structured, and accessible data for analytics and business use Collaborate with cross-functional teams to support analytics, reporting, and AI/ML initiatives Qualifications: Demonstrated experience in data engineering, with a proven ability to build scalable data solutions Strong proficiency in Python and SQL Hands-on experience with Apache Spark (including Structured Streaming) Experience with Databricks (Workflows, Delta Li...