About
Backend & Data Engineer focused on building scalable, low-latency distributed systems and data platforms in production. I’m a Backend & Data Engineer with ~3 years of experience at Apollo 24|7, building low-latency, high-throughput distributed systems and data platforms for a healthcare product serving 30M+ users across India. I specialize in designing and operating backend services, data ingestion pipelines, and platform infrastructure using Java, Python, BigQuery, Kafka, Pub/Sub, PostgreSQL, and Redis, with a strong focus on performance, reliability, and scalability. I’ve owned and operated multiple mission-critical backend and data systems end-to-end, including large-scale ingestion and orchestration pipelines powering analytics and operational workflows. I was the sole owner of the Apollo DAX data platform for several months, responsible for system design, optimization, production support, and platform reliability. These systems delivered measurable business impact — reducing data sync latency from weekly to 30 minutes (~97% improvement), accelerating pipelines from ~30 minutes to ~1 minute through parallel orchestration, and cutting infrastructure costs by ~50% via migration to the BigQuery Storage Write API. With strong expertise in distributed systems, API design, backend optimization, and production debugging, I collaborate closely with cross-functional teams in CI/CD-driven environments, using tools like Docker, Kubernetes, Terraform, Grafana, Kibana, and Graylog to operate systems at scale. I’m deeply interested in backend architecture, data infrastructure, and performance-critical systems, and I thrive in high-ownership, fast-moving product environments. Always open to technical discussions, system design deep dives, and connecting with engineers building at scale.
Work experience
Software Engineer at Apollo 24|7, Jun 2023 - Present · 3 yrs 4 mos, Banglore, - Built and scaled backend systems serving 30M+ users, designing distributed workflows across data pipelines and logistics systems. - Designed a push-based data migration system ensuring zero downtime and eliminating sync inconsistencies across environments. - Reduced data sync latency from weekly to 30 minutes and improved processing time by 97%+ through pipeline automation. - Optimized BigQuery pipelines (Storage Write API + UPSERT), cutting infrastructure costs by ~50%. - Engineered high-scale systems including rate limiting (1M/min → 200/min) and parallel processing (30 min → 1 min), improving reliability and throughput.
Software Development Intern at Apollo 24|7, Jan 2023 - May 2023 · 5 mos, Hyderabad, Telangana, India
