Muhammad Syafiq Farhan Mohd Faridz

Client-facing data engineering and pipeline development supporting enterprise regulatory reporting and data infrastructure migration for financial sector clients. • Migrated enterprise Alteryx Server infrastructure with zero workflow loss across 40+ production workflows, maintaining continuity of critical regulatory reporting pipelines • Designed and optimised ETL pipelines supporting enterprise regulatory reporting for a BNM-regulated financial institution, improving processing reliability and auditability • Resolved 20+ production data issues by root-cause analysis of pipeline logic; reducing recurring failures impacting downstream reporting cycles • Rebuilt inefficient Alteryx workflows in collaboration with client stakeholders, reducing data processing time and improving system stability across reporting runs • Built and maintained automated tax reporting pipelines, reducing manual workload by ~70% and enabling consistent, scheduled execution • Improved pipeline documentation and logic consistency to support data governance and audit readiness under BNM compliance requirements

Applied AI and data engineering research within the Centre of Artificial Intelligence, focused on health analytics systems and AI-powered data pipelines. • Built end-to-end Python data pipelines ingesting from CSV and PostgreSQL sources, implementing structured schema validation to ensure data quality across pipeline stages • Developed REST APIs using FastAPI to expose processed health metrics to downstream frontend and analytics applications • Integrated AI-generated recommendations using LangChain and OpenAI API; delivering contextual, prompt-engineered outputs for staff health reporting • Collaborated across frontend, backend, and database teams to deliver an integrated health analytics platform from ingestion to API-based consumption