◦ Architected & built scalable invoice processing pipeline (AWS Glue, DynamoDB, Lambda, State Machine) to handle high volume data, automating the accounting workflows.◦ Implemented orchestrator lambda that uses randomised scanning reads on DynamoDB to avoid starvation problem and controls the rate at which step functions should be invoked.◦ Leveraged AWS CDK for infrastructure as code to ensure efficient deployment and management.◦ Developed a rate controlled API to handle payout requests for the influencer program, integrated with orchestration tool for invoicing and persisting data to DynamoDB for accounting. Implemented robust exception handling. Saved 576 hours/year for BD team across programs.◦ Implemented hydration of multiple attributes through out the Prime subscription flow so that calculation of various charges can happen on demand during price change.◦ Crafted service integration layers (SILs) for comprehensive orchestration flow management, ensuring smooth execution and state control.◦ Migrated service from CloudFormation templates to CDK with common parametrised constructs which increased developer velocity by easing development, testing, code reusability, and maintenance.◦ Implemented workload isolation strategy for a Tier 1 service using physical isolation, throttling, and cell-based architecture to meet tier-based availability and read/write scalability requirements.

◦ Developed a strategy for reconciliation of data which helped the team to save at least two man-days per week. ◦ Resolved an issue in the deduplication logic used in service consumed by accounting team.