Shaik Iftequar Ahmed

I design and build backend systems with strong focus on high availability, low latency, scalability and distributed across multiple regions. I enjoy working on problems around data pipelines, distributed systems, and event-driven architectures.

Over the past ~3.6 years in Fintech and Audit domains, I’ve built and owned production systems that process millions of transactions and events, where correctness, fault tolerance, and reliability are as critical as performance.

My core stack includes Python, Node.js, TypeScript, FastAPI, Kafka, AWS, Docker, PostgreSQL, MongoDB, Redis, along with monitoring and observability tools like Grafana and Prometheus, and CI/CD pipelines using Jenkins.

Key contributions

• Designed and built a scalable blockchain indexing ETL pipeline handling 5M+ transactions/day, optimized for throughput and data consistency.
• Architected a distributed event ingestion pipeline processing ~10M events/day, leveraging event-driven design for high reliability and horizontal scalability.
• Led code reviews and architecture discussions, helping the team write cleaner code and improve scalability and the reliability of the system

I work best with teams that value end-to-end ownership, clean architecture, and follow design patterns.

Software Development Engineer at Garden Finance (2025-08 – 2026-02)

• Contributed to building a cross-chain atomic swap explorer that indexes smart contract events of 5+ blockchains
• Developed a distributed event ingestion pipeline with Kafka, with a capacity of processing 10M events per day
• Optimized front-end performance by by 60% by implementing code-splitting and lazy loading techniques
• Built reusable UI components and layouts for analytics dashboard pages for showing high volume transactions data
• Led code reviews and architecture discussions, to help improve scalability and the reliability of the system
• Tech Stack: Next.js, Node.js, Kafka, PostgreSQL, AWS, EC2, S3

Software Engineer at Deloitte USI (2022-08 – 2025-08)

• Designed and built a scalable ETL pipeline, indexing blockchain data 80% faster and enabling real-time analytics
• Improved query latency by 95% (4s → 200ms) by transforming raw transaction data into read-optimized tables
• Reduced cloud storage costs by 40% by separating archival and query data based on data access needs
• Increased pipeline reliability through checkpoints and data reconciliation, eliminating data loss and corruption
• Developed reusable ETL workflows, enabling rapid development and integration of new analytics features
• Tech Stack: Node.js, Express.js, React, Kafka, PostgreSQL, MongoDB, Redis, AWS, S3, EC2

Bachelor of Technology in Computer Science and Engineering – VNR Vignana Jyothi Institute of Engineering and Technology (2018-07 – 2022-06)