# Meha Shah

> Senior Backend Engineer | Distributed Systems & Payments | Driving Reliable High-Scale Systems @ Lyft

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/meha

## Work Experience
### Senior Software Engineer @ Lyft
Jan 2020 – Present | San Francisco Bay Area
Backend engineer in the Lyft's payments platform team. Developing innovative monetization products with seamless solutions for billing & invoicing lifecycle, subscription management, transaction fulfillment, payments instrument management.

### Software Engineer @ Cisco Tetration Analytics
Jan 2018 – Jan 2020 | Palo Alto, California, United States
- Worked as a backend software engineer in Tetration Analytics, Cisco's internal startup focused on the mission of simplifying workload security in public and private clouds.
- Developed a cluster health alert and monitoring tool that identifies unhealthy services and sends out alerts to users with potential root cause. The tool also creates Grafana charts for users to help them debug the service failures.
- Developed backend services, end-to-end test framework for Tetration’s Data Backup and Recovery feature, a disaster recovery solution that periodically backs up tetration cluster data to an external S3-compliant storage platform for retrieval upon disaster.
- Developed backend APIs for an Online Drive Replacement feature, which allows the tetration customers to identify, decommission and commission bad drives on the cluster’s server without bringing down the affected server. This feature helps in reducing cluster down time and avoid unnecessary service switchovers and master re-elections when a server fails.

Technologies used: Python, Go, S3, HDFS, MongoDB, OpenTSDB, REST, Grafana, Ansible, Consul, Vault, Jenkins

### Software Engineer Intern @ Starbucks
Jan 2018 – Jan 2018 | Scottsdale, Arizona, United States
- Worked with the Smart Store operations team in the Starbucks’s Business Intelligence domain located in Starbucks, Seattle.
- Implemented a data pipeline to extract the real-time voice data obtained from Alexa voice interface, send it to the Akka based server for data processing using Kafka streams and load the results to the Cassandra database.
- Also, worked with the Chatbot interface team at Scottsdale to integrate Alexa with the Starbucks OpenAPI and provide voice interface to customers to order Starbucks products.

Technologies used: Scala, Kafka, Akka, Cassandra, Alexa Skills, Angular CLI

### Software Engineer Intern @ American Express
Jan 2017 – Jan 2017 | Phoenix, Arizona, United States
- Worked with the Global Acquisition Analytics & Data Science team in AMEX’s Digital Marketing domain.
- Developed a configurable tool which performs data analysis on the raw data obtained from processing millions of browser cookies and visualize the result to understand meaningful patterns.
- The tool helps in suggesting substantial conclusions to support decision making in digital marketing.

Technologies used: Python, Pandas, Apache Hive, Data Analytics, Cronjobs

### Software Engineering Intern @ CYR3CON
Jan 2017 – Jan 2017 | Tempe, Arizona, United States
- Worked with the Operations team responsible to migrate the system to the distributed infrastructure, to develop a scalable and predictive data-driven cyber threat intelligence system to identify and track various cyber threats.
- Responsible for ORM transitioning from PostgreSQL to MongoDB using MongoEngine library.
- Responsible for monitoring and maintaining existing database in Postgres.
- Developed python classes for MongoDB data-pipeline tasks to run them as daily cron jobs over Production server.
- Assessing the performance of the new distributed architecture.
 
Technologies used: Python, MongoDB, Postgres, Map-Reduce

### Research Aide @ Arizona State University
Jan 2017 – Jan 2017 | Tempe, Arizona, United States
- Worked as a Research Assistant with Professor Asim Roy on building a Health Monitoring System in collaboration with Mayo Clinic.
- Implemented the Kohonen Net model (Type of Neural Network) in a distributed environment to train the real time streaming ECG data and used the clustering algorithm alongside to reduce the dimensionality of the data set.
- Assessed the performance and execution time of the Kohonen Training model on the basis of various factors: number of hadoop nodes, memory per node, number of cores per node, number of executors, number of partitions of data.

Technologies used: Scala, Apache Spark, HDFS, Hadoop YARN


## Education
### Master of Science - MS in Computer Science
Arizona State University

### Bachelor of Technology - BTech in Computer Science
Jaypee University of Information Technology


## Contact & Social
- LinkedIn: https://linkedin.com/in/meha-shah

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Source: https://flows.cv/meha
JSON Resume: https://flows.cv/meha/resume.json
Last updated: 2026-03-29