Cloud Data & Platform Engineer

Candidate Description

With over twelve years immersed in data engineering, this professional excels at architecting and implementing cloud-native analytics platforms that leverage a Data Platform, a Data Engineering Platform, a Cloud Platform and a Cloud Service Provider. Their background spans end-to-end data modelling, ELT pipeline development and BI visualisation, enabling organisations such as a Professional Services Firm and a Consulting Firm to unlock actionable insights across finance, HR and operational domains. They bring deep knowledge of Kimball and Data Vault methodologies coupled with strong stakeholder engagement and mentoring abilities.

Technically adept, they deliver robust solutions using tools like dbt, Apache Airflow, a Data Factory, Spark (PySpark) and Power BI. Projects include building a Data Platform lakehouse that ingests a CRM Platform, an HR Platform and an ERP System data, introducing RBAC and SSO governance controls, and automating CI/CD with a DevOps Tool pipelines. Their hands-on optimisation of clustering strategies and materialised views has enhanced query performance, while data-quality frameworks have ensured compliance with GDPR and enterprise standards.

Whether coaching junior engineers or collaborating with cross-functional squads, this individual exhibits a pragmatic leadership style rooted in Agile and ITIL practices. Comfortable navigating diverse industries—from financial services to logistics—they adapt quickly to new challenges, champion DevOps culture and consistently translate complex requirements into scalable, secure and maintainable data platforms. Their blend of technical depth, process rigour and communicative flair positions them as a valuable asset for organisations seeking to maximise data-driven decision-making.