↳Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related technical field; or equivalent training and professional experience
↳5+ years of experience in ETL/ELT, data warehousing, Business Intelligence, and integrating data processing/workflow management tools into pipeline design
↳5+ years building and maintaining end-to-end data systems using Python, Scala, or similar programming languages
↳Solid experience in utilising SQL for data analysis, investigating data issues, diagnosing root causes, and designing effective solutions
↳Experience in working with cloud-based data technologies, preferably on Microsoft Azure, within continuous integration and delivery (CI/CD) environments
↳Demonstrated experience working with large-scale datasets using Databricks, PySpark, Spark Streaming, and Delta Lake
↳Hands-on experience with structured, semi-structured, and unstructured data across various storage systems, including relational databases (RDBMS), data warehouses, in-memory caches, and document databases
↳Familiarity with cloud storage solutions such as Azure Data Lake and Blob Storage
↳Solid understanding of data modelling principles (experience with Data Vault is a plus) and strong skills in system design, implementation, and testing
↳Experience with event-driven architectures (e.g., Kafka, Event Hubs, Apache Flink) and containerised microservices platforms (e.g., Kubernetes, Docker, Helm Charts)
↳Knowledge and practical use of dbt (data build tool), experience with BI tools
↳Excellent communication and collaboration skills, ability to provide technical leadership to other developers
