Data Engineer for a leading pharmaceutical company’s cancer genomics R&D initiative.- Designed and developed an automated data ingestion layer on AWS that eliminated dependency on external teams, reduced wait times by 50-80% and reduced end-to-end pipeline run time by over 30%.- Developed a metadata extraction pipeline that saved several minutes of a frequent task, and was furtherenhanced for robust data validation.- Analysed extant cloud resource usage patterns for analysis runs and recommended cost-optimal EC2 instance and storage options that saved several thousand Dollars per year for the team.

Data operations lead of a team of 3 for a startup working on wearables for workplace safety.- Worked with data scientists to incorporate handcrafted rules and machine learning models into a Spark pipeline on AWS.- Optimised Spark jobs and reduced batch processing times by half.- Designed an audit trail and dashboard to keep track of data being processed which significantly reducedincidents of data corruption.- Successfully led a short-term project in parallel to incorporate models in the AWS Machine Learning Marketplace, as part of a private beta test.