Pranav Sagar

Software Development Engineer
+91-6203131747 pranav.sagar@outlook.com linkedin.com/in/pranavsagar github.com/PranavSagar leetcode.com/u/prnvsgr

Professional Summary

Backend Software Engineer with 2+ years of experience building scalable microservices using Java and Spring Boot. Experienced in distributed systems, Kafka-based event processing, and PySpark data pipelines. Delivered 35-60% cost reductions, handled 800K+ QPS serving 100M+ users, and built reusable frameworks adopted across multiple teams.

Architect and develop high-performance systems with under 30ms p95 latency. Design event-driven architectures with zero-downtime migrations using Kafka, Redis, Aerospike, and gRPC. Build comprehensive observability solutions and optimize system reliability through query optimization and caching strategies.

Technical Skills

Languages Java, Python, SQL, JavaScript Backend & Frameworks Spring Boot, Kafka, Kafka Streams, gRPC, Protobuf, Flask Data Processing Apache Spark, PySpark, ETL Pipelines, Batch Processing Databases & Caching Redis, Aerospike, PostgreSQL, MySQL, ClickHouse Infrastructure & DevOps Kubernetes, Docker, Helm, GCP (GKE, GAR), CI/CD Pipelines Monitoring Prometheus, Grafana, Distributed Tracing, JVM Profiling System Design Microservices Architecture, Event-driven Systems, Circuit Breaker, Dual-Write, API Versioning

Education

M.Tech. Artificial Intelligence & Machine Learning (April 2026 - Present) BITS Pilani — Work Integrated Learning Programme
Bachelor of Technology in Computer Science (CGPA: 9.10 / 10.00) 🥈 Silver Medalist Rajasthan Technical University — Aug 2019 to July 2023

Experience

Sept 2023 – Present
SDE 1 - Backend Developer
Glance, InMobi — Bengaluru, IN
  • Architected and built content enrichment microservice (Java/Spring Boot) from scratch handling 800K+ QPS with under 30ms p95 latency using Kafka, Protobuf, Redis, Aerospike serving 100M+ users
  • Designed dual-write architecture with protocol adapter enabling zero-downtime migration and seamless integration of new data sources across distributed systems
  • Optimized PySpark pipelines reducing compute costs by 35% through DataFrame caching and fixed production memory leak using heap dump analysis
  • Built dynamic configuration service with gRPC powering 10+ microservices, eliminating hardcoded configs and enabling semantic versioning for backward-compatible rollouts
  • Created reusable observability framework with gRPC interceptors and Prometheus metrics adopted across 5+ services; built cache layer reducing API costs by 60%
  • Improved system reliability through event-driven batch processing with stale message detection and query optimization reducing database load by 40%
  • Built GDPR compliance API with region-based access controls, batch processing of 10K+ records, and automated monitoring eliminating manual workflows
  • Deployed release automation platform (Python/Flask) on GKE with Helm and CI/CD pipelines reducing deployment time by 90%; managed Protobuf versioning across 10+ services
Tech: Java, Spring Boot, Kafka, Kafka Streams, gRPC, Protobuf, Redis, Aerospike, PostgreSQL, ClickHouse, PySpark, Kubernetes, Docker, Helm, GCP (GKE, GAR), Prometheus, Grafana, Distributed Tracing
May 2022 – July 2022
ML Engineering Intern
Celebal Technologies — Jaipur, IN
  • Built video recommendation system using machine learning techniques, processing user interaction data to generate personalized recommendations and improving click-through rate (CTR) by 1.4%
Tech: Python, Machine Learning, Recommendation Systems

Projects

Amazon Review Sentiments Analysis
Machine Learning / NLP Project
  • Built sentiment analysis system processing Amazon product reviews using NLP techniques and machine learning algorithms
  • Implemented text preprocessing pipeline with tokenization, stemming, and TF-IDF vectorization for feature extraction
  • Trained and evaluated multiple classifiers (Naive Bayes, SVM, Random Forest) achieving 87% accuracy in sentiment classification
  • Deployed interactive web interface using Flask for real-time sentiment prediction on user-submitted reviews
Tech: Python, NLTK, scikit-learn, Pandas, Flask, NLP, Machine Learning

Achievements

🏆 Avengers Award at Glance (InMobi)
🥈 Silver Medalist - Rajasthan Technical University
📜 Microsoft Certified - Azure AI & Data Fundamentals
💻 LeetCode Rating 1577 (Top 25%)
🥈 Smart India Hackathon 2022 Runner-Up