Lead Data Engineer – AWS & Snowflake

Candidate Description

A versatile data-engineering leader with more than 13 years of experience spanning consulting, telecommunications, insurance, manufacturing and government sectors. Skilled in architecting cloud-native analytics platforms, they combine deep expertise in AWS, Azure, Snowflake and Databricks with strong data-modelling and warehousing capabilities. Their background covers big-data technologies, integrations and end-to-end BI delivery, underpinned by an engineering degree and multiple Microsoft and Snowflake certifications.

Demonstrating advanced technical acumen, this professional has designed and deployed enterprise data-lake and archiving frameworks using ADLS Gen2, Synapse, Spark and Python, while also implementing RESTful APIs through Django on Azure. Key achievements include leading the build of a multi-terabyte insurance data-lake for a Professional Services Firm, optimising Spark-on-Hive workloads for significant performance gains, and rolling out CI/CD pipelines with Azure DevOps that cut deployment effort by over 30 percent. Their toolkit extends to ETL tools such as Informatica, Qlik Compose and SSIS, as well as visualisation solutions in Power BI and Cognos.

Combining leadership with hands-on delivery, they have managed multi-disciplinary teams, mentored junior engineers and coordinated global deployments for organisations like a Consulting Firm, a Manufacturing Company, a Technology Company and a Professional Services Firm. Comfortable operating within Agile, Scrum and SAFe frameworks, they adapt rapidly to diverse domains, from industrial IoT to government compliance. With a proven track record of translating complex data challenges into scalable solutions, they offer employers a strategic blend of technical depth, stakeholder engagement and results-driven execution.