Shantanu Ghar

About Shantanu Ghar

Backend Engineer with 3+ years of experience building scalable distributed systems, cloud-native microservices, and data-intensive platforms. I hold a Master’s degree in Computer Science from Syracuse University and have worked across backend and data engineering teams to deliver high-performance, reliable production systems.My core strength is backend and systems engineering, with hands-on experience in Golang, Python, and Java, designing RESTful APIs, microservices, and internal platforms on AWS and GCP. I’ve owned services end-to-end — from low-level design and implementation to CI/CD, monitoring, and cost optimization — delivering outcomes such as 90% reductions in data processing time and significant cloud cost savings.Alongside backend systems, I bring strong data engineering experience, having built and optimized ETL pipelines, distributed data processing workflows, and federated query engines using Apache Spark, SQL, and cloud-native data services. My work has focused on improving throughput, reliability, and observability for data-heavy workloads at scale.I enjoy working at the intersection of backend infrastructure and data platforms, solving ambiguous problems that require strong system design, performance tuning, and cross-team collaboration. I’ve been recognized for technical innovation through multiple national-level hackathons, including NVIDIA AI Hackathon and I-Hack (IIT Bombay).I’m actively seeking Backend Engineer / Software Engineer roles, with openness to data-focused or platform teams, where I can work on scalable systems, cloud infrastructure optimization, and data-intensive services.Core expertise: Backend Engineering · Distributed Systems · Golang · Python · Java · Cloud (AWS/GCP) · Microservices · System Design · ETL · Data Platforms · CI/CD · Big Data

Experience

1. Software Engineer

   LiveRamp

   Oct 2024 — Present · Seattle, WA, US

   Designed and implemented a migration service to transition legacy Dataproc-based ingestion workflows to SingleStore pipelines, reducing end-to-end data processing time by ~90% for customer workloads.Led cloud infrastructure benchmarking across multiple VM families and compute profiles to identify optimal cost-throughput tradeoffs, cutting infrastructure costs by ~50% while meeting strict SLA requirements.Built production-grade observability (alerts, dashboards, runbooks) using Grafana and GCP, improving on-call response quality and reducing mean-time-to-resolve (MTTR) by ~30%.Owned system reliability and operational readiness, including SLA enforcement, failure handling, and incident documentation for customer-facing data pipelines.Tech: Python, SQL, SingleStore, GCP, Grafana, Terraform, Distributed Systems

Education

• Syracuse University

  Master's degree, Computer Science

• SIES Graduate School Of Technology

  Bachelor of Engineering - BE, Computer Science

  2016 — 2020