Digital Data Engineer

Candidate Description

With over a decade delivering value across the energy, transport and logistics sectors, this data-driven professional blends engineering rigour with modern analytics to build scalable data products. Fluent in Python, SQL, Azure (ADF, Synapse, Databricks) and Snowflake, they design and operationalise ELT pipelines, geospatial analytics and AI-driven workflows that empower decision-makers. Their multilingual communication skills in English, Vietnamese and Chinese complement a strong record of cross-functional collaboration.

Adept at architecting end-to-end solutions, they have delivered KNIME-powered geospatial data pipelines for a Major Energy Company, Power Platform business applications for a Housing Organization and predictive warehouse optimisation models for a Consulting Firm. Their toolkit spans Airflow orchestration, Docker-based deployments, Terraform infrastructure automation and advanced BI using Power BI and Streamlit, all underpinned by agile ways of working supported with Jira and Confluence. Key accomplishments include automating LiDAR processing for field crews, reducing manual bill ingestion efforts through AI Builder automations and boosting warehouse picking efficiency with data-science-driven slotting models.

Combining leadership in solution design with a keen eye for continuous improvement, they mentor teams on best practices in data governance, testing automation and CI/CD. Adaptable across greenfield and brownfield environments, they thrive on complex challenges that require both strategic thinking and hands-on execution. Employers benefit from a versatile engineer who consistently translates business requirements into resilient, insight-rich data assets that drive operational excellence and competitive advantage.