Harvey Lam
Data Solutions Architect Manager, Tech & Data Hands-on Technical Lead (Python Azure Sql) @Deloitte
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WORK HISTORY
Data Solutions Architect Manager, Tech & Data Hands-on Technical Lead (Python Azure Sql) @Deloitte
End-to-end \"Zero-to-One\" Architect. I own the overarching data strategy and hands-on Python engineering for Enterprise Value Creation, leveraging a lean 2-person pod for standardised tasks.VALUE CREATION & DUE DILIGENCE- Engineered a Python and YAML-based Data Quality Check (DQC) framework on Azure Synapse. Reduced global validation execution from manual hours to a 15-minute automated pipeline, guaranteeing 100% data lineage and operational transparency for liquidity events- Translated financial requirements into scalable technical roadmaps, directly driving Commercial ROI through Data Architecture.ERP LEGACY MODERNIZATION- Reverse-engineered on-premise SAP and Oracle ERPs to extract trapped enterprise data- Developed custom Python automation for extraction configurations, slashing technical setup time by 94%(1.5 hours to 5 minutes) and reducing review cycles to 5 minutes- Standardized extraction protocols and authored documentation to successfully offload routine workloads to a centralized support center.CLOUD ARCHITECTURE & ENGINEERING RIGOR- Architected and deployed modular Azure Synapse, PySpark, and SQL data pipelines for enterprise dataset processing- Enforced production-grade engineering standards (CI/CD, Docker, Git), shifting the culture from ad-hoc scripting to resilient software delivery- Built Power BI dashboards integrated with Azure DevOps to surface real-time engineering metrics for C-suite stakeholders.STAKEHOLDER ENGINEERING- Acted as the technical bridge between Partners/CFOs and IT Security, neutralizing infrastructure blockers to accelerate time-to-value.
EDUCATION
HKTA Tang Hin Memorial Secondary School
High School
The University of Hong Kong
Bachelor's degree, Economics and Finance
SKILLS
ABOUT HARVEY LAM
I act as the bridge between non-technical Partners/CFOs and rigid IT Security teams, combining the commercial acumen to define \'why\' we build with the technical depth to execute \'how\' we build. End-to-end \"Zero-to-One\" Architect. I own the overarching data strategy and hands-on Python engineering for Enterprise Value Creation, leveraging a lean 2-person pod for standardised tasks.ERP DATA ENGINEERINGI specialize in extracting value from complex environments. By developing custom Python packages, I automated data extraction configurations for proprietary tools, slashing technical setup time by 94%(from 1.5 hours to just 5 minutes) and reducing review cycles to minutes. I also standardized these extraction protocols with comprehensive documentation, successfully offloading routine workloads to a centralized support center.LEGACY MODERNIZATIONI drive large-scale migrations from rigid on-premise legacy systems to scalable, modern cloud environments. I specialize in reverse-engineering complex SAP and Oracle ERPs to unlock trapped enterprise value, ensuring legacy operations are fully modernized and positioned for portfolio growth.CLOUD DATA ARCHITECTUREI architect and deploy modular data pipelines using Azure Synapse, PySpark, and SQL. To guarantee operational transparency and exit-readiness, I engineered an enterprise-grade Data Quality Check (DQC) framework using Python and YAML. This standardized global validation protocols, reducing execution times from several manual hours to a reliable 15-minute automated pipeline.STAKEHOLDER ENGINEERINGI act as the critical translation layer between Finance leadership and IT Security, neutralizing technical objections to accelerate time-to-value. To ensure C-suite alignment, I built high-fidelity Power BI dashboards integrated directly with Azure DevOps, surfacing real-time engineering and delivery metrics for senior stakeholders.APPLIED AI INFRASTRUCTUREI focus entirely on building the pristine \"data plumbing\" required to make applied AI commercially viable. Currently, I am building \'Sentinel\' on GitHub: an AI-augmented reference architecture exploring orchestration patterns for integrating LLMs (RAG) into legacy enterprise stacks.
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