Flipkart Health Plus | Python, Flask, FastAPI
At Flipkart Health Plus, I worked on backend logistics systems that sat between sellers, fulfillment centers, and external 3PL partners. The core problem was simple but high-impact: the promised delivery date shown to customers had to be realistic and consistently correct.
A big part of my work was building integrations with logistics partners to get near real-time serviceability and shipment-status signals, then using that data to continuously improve SLA prediction accuracy. Better SLA accuracy directly improved customer trust and satisfaction because customers received dates that matched actual delivery performance.
What I Worked On
- Built and maintained MongoDB and RDBMS sync workflows so shipment parameters and statuses remained consistent across internal systems and external partner feeds.
- Integrated 3PL APIs for Delhivery, Ekart, and Bluedart to support shipment creation, tracking, and serviceability checks from a single internal workflow.
- Reworked the SLA engine for third-party logistics providers across India and exposed SLA calculations through FastAPI services used by downstream systems.
- Designed Pub/Sub-based event processing to consume logistics events and update shipment states for both forward and reverse journeys.
- Built seller-specific SLA customization logic that accounted for local holidays, seller operations, and Sunday working schedules.
- Worked on stored procedures, BigQuery analysis, and AWS CloudWatch-based debugging to diagnose unserviceable regions and production delivery exceptions.
- Contributed to stronger coupling between the Healthbuddy operating model, fulfillment centers, and 3PL integrations, improving end-to-end shipment lifecycle consistency.
- Helped improve delivery-date prediction accuracy, which translated into better SLA adherence and higher customer satisfaction.