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• Developed scalable data solutions, automating ETL processes to migrate data across platforms using Snowflake. • Engineered scalable data pipelines, integrating from various source systems such as Oracle, Postgres, MSSQL data into a centralized warehouse, enhancing data flow efficiency using AWS services. • Automated internal workflows using Python, saving 20+ hours of manual work weekly, significantly improving operational efficiency. • Troubleshot ETL failures and data discrepancies from SIS and finance systems, reducing recurring issues by 30%. • Built custom ELT pipelines in AWS environment improving data transformation speeds by 35%. • Identified and resolved data quality issues, performing root cause analysis and implementing automated monitoring scripts. • Designed, tested, and maintained scalable data engineering pipelines to meet complex business requirements.

• Established data integration methodology using Snowflake, streamlining data flow and accessibility. • Computed 300+ derived metrics using Python for data processing and transformations, delivering actionable insights through Tableau reports. • Automated RNA sequencing data pipelines, boosting data processing speed and accuracy by 20%. • Collaborated with scientists to standardize data structures, ensuring seamless integration and analysis.

• Led functional and UI testing, ensuring smooth processes and accurate results across sprint cycles. • Automated test scripts with TOSCA, reducing manual testing by 40% and accelerating the testing cycle. • Collaborated with cross-functional teams to align business requirements with test execution. • Validated core functionalities for a product launch generating AUD 40M in annual revenue, ensuring a seamless user experience and mitigating risks.