Designed and built a central delivery-defect tracking system for Amazon’s Transportation Network to track re-occurring delivery defects - which can be caused by virtually any failure in the chain from ordering to final doorstep fulfilment, and aims to reduce the Repeat Defects Rate (RDR)

• Developed a unified data ingestion and persistence solution for aggregating address data obtained from diverse third-party sources, to aid the creation of an authoritative catalogue of addresses at Amazon. Proposed key optimisations to the data ingestion and streaming process which reduced the ingestion time by 80%, while working with address data in excess of 2TBs for address catalogue bootstrap• Led the expansion of Amazon Shipping into European markets, unlocking markets of 22.7MM and 26MM annual MFN parcels, respectively. Collaborated with cross-functional teams and business stakeholders to align on expansion strategies• Streamlined the update process for address attributes by shifting to an update-event based architecture, reducing SLAs from 4-5 days to a few hours and managing approximately 600 million updates.• Delivered an effort reduction of roughly 10 hours of manual work per week for salesforce admin teams by enhancing a data synchronisation pipeline.• Regularly mentored interns and new-hires helping them on-board onto the team and grow in their role.

Worked as part of Shipper Performance team towards building a solution for identifying the shippers who over-forecast their shipping volumes regularly with an aim to promote better planning and forecasts to reduce the overall shipping costs.

Enhanced the CI/CD automation script for a pipeline using Python, Bash scripting, and linux text processing utilities.