Summary
Shamir Alavi is a technical lead with 11 years of experience building data platforms, ETL pipelines, and governance solutions across public sector, banking, and prop-tech. Currently leading data quality and governance initiatives at CPP Investments, he specializes in integrating automated validation into ETL and BI workflows to make analytics more reliable and auditable. His background includes migrating complex on-prem systems to AWS at BMO, architecting Digital Twin data platforms at a startup, and advancing AI-driven anomaly detection and explainability at the Canada Revenue Agency. He pairs hands-on engineering with team leadership—rising from data engineer to tech lead within five years—and has led multi-disciplinary teams on RAG/LLM projects and real-time incident systems in open source. Notably, he prototyped an LLM for CERN’s Ganga workload manager and spearheaded a 200+ book RAG Q&A effort, reflecting a blend of production data engineering and experimental ML work.
11 years of coding experience
9 years of employment as a software developer
Master of Applied Science Data Science, Master of Applied Science Data Science at Carleton University
Bachelor of Technology (B.Tech.) Electrical Engineering, Bachelor of Technology (B.Tech.) Electrical Engineering at National Institute of Technology Silchar
English, Japanese, Spanish