Work Experience
Experience spanning data engineering in large-scale environments and analytics-focused work in a research and insights setting.
Data Team Intern — IBISWorld (Melbourne)
2025- Delivered Snowflake ELT workflows using AWS S3 external tables, improving ingestion efficiency and reducing unnecessary storage duplication by ~20–25% across recurring loads.
- Parsed and flattened complex multi-level JSON using LATERAL FLATTEN, increasing usable analytical fields by ~35% and cutting manual preprocessing time by ~30% through a structured multi-layer data flow (staging → parsing → transformation).
- Enhanced pipeline traceability with structured logging and clear transformation checkpoints, reducing debugging time by ~25% and supporting faster onboarding via high-level architecture documentation.
Data Engineer — nbn Australia (via Infosys)
2021–2023- Built and maintained AWS S3 → EMR → Redshift ETL pipelines supporting financial and reporting teams, achieving ~99% successful daily run stability across batch workloads.
- Optimised SQL transformations and Redshift table structures (sort/distribution keys), improving end-to-end pipeline runtime by ~25–30% on recurring data loads.
- Developed and managed 50+ SQL scripts including delta-load logic, DDLs, and control-table updates in MySQL, ensuring alignment with E-R designs and JIRA user stories.
- Reduced manual intervention during executions by ~40% through parameterising ETL behaviour with YAML/JSON configs and automating jobstreams in IBM Workload Scheduler.
- Enhanced data quality and reduced SIT→UAT defect leakage by ~30% by validating missing data, identifying upstream design gaps, and coordinating fixes with analysts and operations teams.