# Upender Mula

> Software Engineer @Stripe | ex-Meta | Python Full-Stack (FastAPI, Django, React, Node.js) | Cloud & DevOps (AWS, Docker, Kubernetes) | Open to New Opportunities

Location: San Francisco, California, United States
Profile: https://flows.cv/upender

Software Engineer with 5 years of experience building scalable backend services, real-time data pipelines, and full-stack applications across financial, risk, and content moderation platforms. Skilled in Python (FastAPI, Django, Flask), Node.js, React.js, TypeScript, and experienced with databases, APIs, and cloud-native systems.

At Stripe, I engineer and scale backend microservices that power global financial reporting, risk scoring, and anomaly detection—working with FastAPI, Django REST, Kafka, Spark, PySpark, PostgreSQL, MongoDB, AWS, Docker, Kubernetes, Terraform, and CI/CD pipelines to improve performance, reliability, and automation.

Previously at Meta, I designed and deployed real-time moderation systems for Facebook and Instagram using Flask, FastAPI, React, Kafka, Celery, Redis, PySpark, and AWS, enhancing compliance reporting and operational efficiency while mentoring junior engineers.

I thrive at the intersection of backend engineering, cloud infrastructure, and data-driven systems, delivering secure, resilient, and high-performing solutions.

Core Expertise
✅ Full-Stack Development – Python, FastAPI, Django, Flask, Node.js, React.js, TypeScript
✅ APIs & Microservices – REST, GraphQL, Event-Driven Architecture
✅ Data Pipelines – Kafka, PySpark, Airflow, Redis, PostgreSQL, MongoDB
✅ Cloud & DevOps – AWS, Docker, Kubernetes, Terraform, CI/CD, Observability
✅ Security & Reliability – OAuth2, JWT, TDD/BDD, ELK, Prometheus, Grafana

I’m passionate about solving complex engineering challenges, mentoring teams, and driving impact through clean code, automation, and scalable architectures.

## Work Experience
### Software Engineer @ Stripe
Jan 2024 – Present | United States
At Stripe, I engineer and scale backend services and microservices using Python (FastAPI, Django REST Framework) and Node.js to support global financial reporting, risk scoring, and anomaly detection. I design and optimize RESTful and GraphQL APIs, integrate Kafka event streams with Python consumers, and build real-time analytics pipelines with Apache Spark, PySpark, Kafka Streams, and Redis, improving reporting speed and reliability.

I manage PostgreSQL for structured reporting data and MongoDB for flexible metadata, while developing interactive dashboards in React.js, TypeScript, Chart.js, and Material UI to deliver live insights into anomalies, exposure metrics, and compliance trends. On the infrastructure side, I package and deploy services with Docker on AWS (EKS, Lambda, SQS, S3, CloudWatch), automate deployments with Terraform and GitLab CI/CD, and enhance reliability with Celery and RabbitMQ for job scheduling and retries.

My role also involves implementing secure authentication and role-based access control (OAuth2, JWT), building backend tooling for data validation and reconciliation, and maintaining comprehensive test suites with Pytest, unittest.mock, and Selenium to ensure accuracy of pipelines, financial calculations, and workflows.

### Software Engineer @ Meta
Jan 2020 – Jan 2023
At Meta, I designed and deployed large-scale content moderation systems that ensured safe and compliant experiences across Facebook and Instagram. I built and optimized Flask and FastAPI REST APIs to enable real-time classification, flagging, and routing of posts, while developing React and TypeScript dashboards for moderation teams to review flagged content, audit actions, and monitor compliance.

I engineered high-throughput asynchronous pipelines with Kafka, Celery, and Redis, reducing response latency by 28% and supporting near real-time moderation. I also designed PostgreSQL and MongoDB schemas for moderation logs and audit trails, ensuring GDPR and CCPA compliance with high query efficiency. To accelerate data workflows, I automated pipelines with PySpark and Airflow, cutting preparation time by 40%.

On the infrastructure side, I leveraged AWS (S3, Redshift, DynamoDB) for scalable storage and analytics, containerized services with Docker, and orchestrated deployments on Kubernetes with automated CI/CD pipelines via Jenkins and GitHub Actions, achieving 99.95% uptime. I strengthened system security with OAuth2, JWT, and RBAC, and improved reliability through observability and monitoring using Prometheus, Grafana, ELK, and OpenTelemetry.

Additionally, I enhanced API resilience with unit and integration testing (Pytest, unittest), and mentored junior engineers on Python microservices, React, Kubernetes, and AWS best practices, boosting onboarding efficiency and accelerating project delivery.


## Education
### Master's degree in Computer and Information Sciences
Saint Louis University
Jan 2023 – Jan 2025


## Contact & Social
- LinkedIn: https://linkedin.com/in/upender9

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Source: https://flows.cv/upender
JSON Resume: https://flows.cv/upender/resume.json
Last updated: 2026-03-22