Portrait of Girija Shankar Tumma

Girija Shankar Tumma

NU Northeastern University
SRM SRM University
View LinkedIn ›
1M+
User interactions served
<200ms
P99 response latency
40%
Database load reduced
68%
Processing time cut
99.9%
System reliability
25%
Fewer deploy errors
Summary

Software Development Engineer with 3+ years of experience designing and building scalable distributed systems, microservices architectures, and cloud-native applications on AWS. Expert in system design, backend optimization, and data pipeline engineering using Python, SQL, and modern DevOps practices. Proven track record delivering high-performance, production-ready solutions with measurable impact on system reliability and performance.

Stack

Software Development

PythonSQLC++Java OODDesign PatternsDSASystem Design

Cloud & Infrastructure

AWSDockerKubernetesAzure GCPApache SparkDatabricksAWS CDKLinux

MLOps & CI/CD

MLflowAirflowGitLab CI GitHub ActionsJenkinsGit

Data & Analysis

Spark SQLETL PipelinesUnit Testing Code ReviewsAgileDebugging

ML & Generative AI

LangChainLlamaIndexTransformers PyTorchTensorFlowAI Agents
Experience
Software Engineer
Feb 2026 — Present
IpserLab Startup, LLC — Remote, Mountain View, CA
  • Designed and developed backend services and REST APIs using Python, Flask, and React, processing over 1M user interactions while delivering personalized experiences with sub-200ms latency.
  • Built distributed data processing pipelines using Apache Spark (PySpark), AWS S3, and Amazon Redshift, improving data processing workflows and increasing retrieval performance by 35%.
  • Developed and optimized SQL queries through indexing and schema optimization, reducing database load by 40% during peak workloads.
  • Created automated testing frameworks using PyTest with unit, integration, and API test coverage to improve software reliability and deployment confidence.
  • Built CI/CD pipelines using Docker, Jenkins, and AWS CDK, automating service deployments and reducing production deployment errors by 25%.
  • Implemented monitoring and logging using Amazon CloudWatch to analyze application metrics, troubleshoot production issues, and improve system reliability.
  • Collaborated in Agile development through system design discussions, code reviews, sprint planning, and production issue resolution while following software engineering best practices.
Software Engineer Co-op
Jan 2025 — Aug 2025
IpserLab Startup, LLC — Remote, Mountain View, CA
  • Designed and deployed backend microservices on AWS EC2 and Lambda using AWS CDK and Linux, reducing workflow processing time by 68%.
  • Developed scalable backend applications and distributed data pipelines using Python, Spark SQL, and Databricks, increasing data throughput by 40% while maintaining 99.9% system reliability.
  • Built cloud-native applications using Docker, Kubernetes, Apache Airflow, and GitLab CI/CD to improve deployment automation and software delivery efficiency.
  • Developed REST APIs, ETL workflows, and database integrations with automated validation processes to improve reliability across distributed application components.
  • Created automated testing solutions using PyTest for unit, integration, and API testing, improving code quality and supporting reliable production releases.
  • Implemented monitoring and logging using AWS CloudWatch to identify performance bottlenecks, troubleshoot failures, and improve application availability.
  • Collaborated with engineering teams on system design, debugging, code reviews, and production support to deliver scalable and maintainable software solutions.
Software Engineer
Jun 2021 — Jul 2023
Cognizant — Hyderabad, India
  • Developed and optimized backend data processing workflows and enterprise ETL pipelines using SQL and AWS services supporting large-scale business applications.
  • Automated data validation and quality monitoring processes, improving data reliability while reducing manual troubleshooting efforts.
  • Designed and optimized SQL queries for high-volume datasets, improving database performance for enterprise reporting and analytics.
  • Configured and maintained AWS infrastructure including EC2 instances and AWS Glue jobs supporting reliable cloud-based data processing.
  • Investigated production issues through debugging, log analysis, and root cause analysis, implementing fixes that improved application stability.
  • Collaborated with cross-functional Agile teams throughout software development, testing, deployment, and continuous improvement initiatives.
Projects
Systems / SQL

Airport Management System

Sep 2025 — Dec 2025

Relational database system for flight scheduling, passenger bookings, staff assignments, and resource allocation. ER diagrams, stored procedures, triggers, and secondary indexing for query performance.

Column-level encryption for sensitive data. 10+ Tableau dashboards covering delay impact, seasonal trends, and revenue optimization modeling.

Deep Learning · Published

Air Pollution Prediction Using Deep Learning

Dec 2021 — Jul 2022

Hybrid CNN-LSTM model predicting PM2.5 levels from AQI data across Beijing monitoring stations — CNNs for spatial features, LSTMs for temporal patterns.

Analyzed multi-station correlations to improve model reliability and forecasting accuracy.

📄 IEEE MysuruCon 2022 Publication ›
VLSI / Hardware

VLSI Design Lab Project

Jan 2021 — May 2021

CMOS inverter design & MOSFET characterization in Cadence Virtuoso — simulated 90nm NMOS/PMOS transistor behavior (ID-VGS, ID-VDS).

Extracted Vth, Vdsat, noise margins, propagation delay, and dynamic power across VDD, temperature, and sizing ratios via DC and transient analysis.

IoT / Embedded

IoT-Based Water Monitoring System

Dec 2020 — May 2021

Arduino Uno–based automated irrigation system using soil moisture and water level sensors for real-time, threshold-based pump control.

Integrated ESP8266 for remote cloud monitoring, with fail-safe logic to prevent dry-run conditions and reduce water waste.

Image Processing

X-Ray Image Denoising using MATLAB

Dec 2019 — Apr 2020

Denoising system for medical X-ray images using Total Variation methods, Wavelet Transform, and PCA to reduce noise while preserving diagnostic features.

Applied probabilistic and statistical models to improve accuracy in digital signal & image processing workflows.

Certifications

Cloud & Data

AWS Certified Developer – Associate (Training)
Udemy · Nov 2021
Big Data Complete Course
Udemy · Aug 2021

AR / VR

Beginner's Guide to Augmented Reality with Unity
Udemy · Apr 2021
Certificate of Achievement in AR & VR
ProProfs · Nov 2020

Mobile Development

Build a Social Network with Flutter & Firebase
Udemy · Jan 2020
Flutter Development Using Dart — Certificate of Graduation
The App Brewery · Apr 2020
Education
Master of Science, Information Systems
Sep 2023 – Dec 2025
Northeastern University, Boston, MA · GPA 3.515 · Data Science, Cloud Computing, DBMS, Machine Learning
B.Tech, Electronics & Communication Engineering
Jun 2017 – May 2021
SRM University, India · OOD, DSA, Deep Learning, Agile