Senior Data Engineer

Candidate Description

With more than fourteen years immersed in data engineering and architecture, this professional combines deep expertise in cloud data platforms with a proven record of modernising analytics environments across gaming, healthcare, government and financial-services sectors. They excel in translating complex business requirements into enterprise-grade solutions, leveraging platforms such as Azure, AWS, Snowflake and Databricks while grounding every design in robust modelling practices that span Data Vault 2.0, dimensional and 3NF methodologies.

Their technical acumen is reflected in hands-on mastery of Azure Data Factory, Databricks PySpark, Matillion and DBT, supported by a toolkit that includes Kafka, Jenkins and GitHub Actions for industrial-strength CI/CD. Key achievements include architecting a Databricks Lakehouse migration, building national-level reporting EDWs for a Primary Health Network on Azure, and standing up a greenfield Snowflake warehouse for an insurance company. They back these deliveries with disciplined SDLC and Agile practices, rigorous data-quality frameworks and meticulous documentation that fosters transparency and auditability.

Equally comfortable leading teams or engaging directly with C-suite stakeholders, this individual demonstrates strong communication and mentoring capabilities, guiding analysts, engineers and testers toward shared delivery goals. Their adaptability across industries and toolsets, coupled with NV1 security clearance, positions them as a versatile asset capable of rapidly delivering secure, scalable and insight-driven data solutions that unlock tangible business value.