Cloud Data Engineer

Candidate Description

With more than eight years navigating data engineering and business intelligence landscapes, this professional excels in architecting cloud-native analytics solutions on Microsoft Azure. They possess deep expertise across the full SDLC, specialising in SQL development, dimensional modelling and the design of scalable pipelines with Azure Data Factory, Databricks and Synapse Analytics. Experience spans diverse domains including healthcare, government and financial services where they consistently transform raw information into actionable insights through advanced Power BI visualisations.

Their technical acumen is showcased through the delivery of lakehouse architectures, CI/CD-enabled ETL frameworks and performance-tuned data models. Adept at Python/PySpark, CI/CD automation with Azure DevOps and GitHub Actions, and governance of Kimball-style star and snowflake schemas, they have successfully led initiatives for organisations such as a Health Organization, an Environmental Agency and a Finance Company. Key achievements include eliminating manual data refresh cycles via automated Delta Lake processes, reducing report load times through DAX optimisation, and enhancing data reliability with robust version-controlled deployment strategies.

Coupling strong communication with collaborative leadership, this individual regularly partners with cross-functional stakeholders to translate complex requirements into elegant technical designs. They mentor junior developers, champion Agile practices and thrive in fast-paced environments that demand both innovation and precision. Ultimately, they bring a proven ability to drive data-driven decision-making, optimise operational performance and deliver measurable value across consulting, government and healthcare sectors.