Context
Partner integrations in insurance environments need to handle varied payloads, asynchronous callbacks, retries, delayed messages, and operational exceptions without losing traceability. My work has focused on strengthening these backend workflows and giving operations teams better tools to understand and recover from failures.
What I worked on
- Built configurable partner-validation and callback workflows, including conditional rules, payload transformation, and AES/RSA encryption with secrets managed through AWS Secrets Manager.
- Improved queue reliability with deferred processing, message replay, dead-letter handling, multi-record SQS processing, and fallback paths.
- Improved service observability using structured Winston logs, OpenTelemetry, SigNoz, and request-scoped context.
- Automated partner reconciliation using a NestJS service with scheduled IST execution to compare forward and reverse feeds across 13 partner application IDs and 21 node groups; distributed reports through Amazon SNS.
- Delivered production fixes for HDFC partner workflows and built a secured endpoint to batch-reprocess failed CRM triggers, supporting batches of up to 2,000 leads with dry-run validation.
- Revamped four Elixir admin modules using React 19 and TypeScript, delivering reusable components, custom hooks, pagination, filters, activity logs, and lead diagnostics.
Selected engineering outcomes
The production platform handled more than 50 million lead records. Resilient SQS processing, retries, replay, and dead-letter handling strengthened lead-processing reliability by 30%. Across four AWS Lambda functions, reusing a shared OpenTelemetry Lambda layer reduced deployment ZIP sizes by 77–83% and cut instrumentation initialization from approximately 750 ms to 80 ms. The reconciliation workflow covered 13 partner application IDs and 21 node groups, while a secured reprocessing endpoint supported batches of up to 2,000 leads with dry-run validation.
Engineering principles
The recurring themes in this work are explicit failure handling, traceable workflows, secure configuration, safe operational recovery, and measuring the cost of instrumentation. These are the principles I aim to bring to backend systems I build.
Confidentiality note
This case study intentionally abstracts client-specific architecture, partner identifiers, payload formats, and internal system details. It describes my responsibilities and the engineering themes without reproducing proprietary implementation material.