Rohit Sharma

Own end-to-end data architecture for a production fintech platform, including transactional PostgreSQL modeling, GCP BigQuery analytics/reporting, and data governance for sensitive financial data. Designed an IST-aware BigQuery reporting layer with pre-join deduplication to resolve multi-source discrepancies and ensure reporting accuracy. Established performance/scalability patterns using composite/partial indexing, partitioning, and concurrent partition-level index builds. Architected event-driven data delivery using Outbox → RabbitMQ → Celery for guaranteed processing of payment and collection events. Defined data-quality, governance, and access-control standards; owned reporting SLAs and data accuracy; built a system health check dashboard for leadership and investors. Mentored engineers on data modeling and SQL best practices and coordinated with stakeholders and partners.

Designed data pipelines and stored-procedure workflows for loan disbursement, payment collection, and notification tracking. Introduced partitioning and indexing strategies to scale transactional workloads.

As Sr. Technical Lead, I lead a 17-member team delivering data analytics, dashboarding, and data architecture for a fintech application that manages merchant payments and reminders. I architect end-to-end data pipelines using Python/Django with PostgreSQL and MongoDB on AWS, develop APIs in Python/Node.js, implement auto-provisioning workflows for new merchants, and monitor system health via dashboards for investors and management. I also introduced API health checks and measures to track critical performance, supporting faster resolution of production issues and improved reliability. My responsibilities include requirement gathering, project planning, and coordinating with internal stakeholders (CEO/CTO) and external vendors to ensure on-time delivery and scalable data solutions.