Aayush
Kapoor
Results-driven Data Engineer and Analytics Lead with deep expertise in Snowflake, cloud data platforms, and business intelligence. Currently serving as Lead Data Engineer at VFMC — a government investment firm managing ~AUD 100B in assets — delivering enterprise data solutions that drive investment analytics, risk management, and executive decision-making. Ten years building end-to-end data systems across banking, finance, and education.
Serving as Lead Data Engineer at a government investment firm managing ~AUD 100B in assets under management. Designing and delivering scalable enterprise data solutions on Snowflake that support investment analytics, risk management, and C-suite decision-making — including data marts sourced from externally procured market datasets exceeding AUD 14M annually.
Driving large-scale warehouse modernisation: Star/Snowflake schema design, virtual warehouse optimisation, micro-partitioning, RBAC, data masking, and cost tuning. Embedded DevOps and DataOps practices using dbt, CI/CD pipelines, and infrastructure-as-code. Regularly engaged CIOs, Heads of Analytics, and Finance executives to translate architecture into business outcomes.
Led high-impact projects including KYC data migration from Siebel to GoldTier, complex CRM migration to Salesforce, and a meticulous APRA data remediation initiative in response to regulatory fines — managing live parallel systems to ensure data quality and compliance. Automated KPI report generation and built Power BI dashboards for operational reporting.
Replaced manual ETL with serverless AWS Glue pipelines. Built an NLP classification model in Python to auto-route student support tickets by department. Digitised the entire enrolment and admission form workflow via Python-based PDF-capture scripts, eliminating hours of manual data entry and improving data quality.
Built QlikView dashboards for strategic client decision-making. Developed SPSS data-wrangling scripts and custom EFM diagnostic surveys. Led the complete rebranding of diagnostic tools during the Gartner–CEB acquisition — delivered four days ahead of schedule. Automated survey creation with Python, reducing daily effort from 8 hours to 1 hour.