● Engineered real-time billing analytics platform with Python (FastAPI, Django REST), GraphQL (Ariadne), and Kafka Streams, delivering subscription insights with <15 min latency and <300ms query response times — increasing finance team reporting efficiency by 40%.

● Designed and exposed scalable APIs (REST + GraphQL), integrated with Stripe Radar APIs & Stripe Sigma, enabling fraud detection, reporting, and advanced customer analytics used by 10+ enterprise clients.

● Built front-end features with React.js + TypeScript, integrating dashboards and data visualizations for live subscription metrics and financial reconciliation.

● Orchestrated event-driven data pipelines using Kafka, Redis Streams, PySpark, and Celery to process millions of subscription updates with guaranteed delivery and retries — reduced processing failures by 75%.

● Optimized data storage and querying by leveraging PostgreSQL, MongoDB, Snowflake, AWS S3, and Apache Pinot, ensuring high availability for multi-tenant systems at scale and cutting query costs by 20%.

● Applied AI/ML techniques (Scikit-learn, PyTorch) to build anomaly detection and fraud risk scoring models on top of billing data streams, reducing false positives in fraud detection by 35% and improving chargeback prevention.

● Automated deployments using Docker, Kubernetes (EKS), Helm, and Terraform (IaC) with CI/CD pipelines (GitLab + GitHub Actions), achieving zero-downtime rollouts.

● Strengthened security & compliance by implementing OAuth2, JWT, RBAC, and ensuring adherence to PCI DSS and GDPR standards with encrypted storage and secure key management.

● Enhanced observability with Prometheus, Grafana, CloudWatch, ELK, and Datadog, reducing MTTR by 60% through proactive alerting and anomaly detection.

● Practiced Agile/Scrum (Jira) and collaborative DevOps culture, participating in sprint planning, peer code reviews, and authoring design documentation for cross-team knowledge sharing.

● Built security-focused full stack applications with Python (FastAPI, Django REST, Flask), GraphQL (Ariadne), React.js + TypeScript/Redux, enabling developers to visualize and triage static analysis findings in real time.

● Designed and optimized RESTful & GraphQL APIs with SQLAlchemy and PostgreSQL/MySQL, exposing taint-flow results to internal CI/CD pipelines and developer tools.

● Engineered scalable data-flow analysis modules using PySpark, Celery, and Kafka Streams, reducing analysis latency by 35% across millions of lines of Instagram’s Django/Python code.

● Integrated Redis / Redis Streams for caching and streaming intermediate results, improving throughput and reducing falsepositive detection rates.

● Applied AI/ML techniques (Python, Scikit-learn, PyTorch) to prioritize high-risk vulnerabilities and reduce noise, cutting false positives in static analysis alerts by 40%.

● Managed structured/unstructured storage with PostgreSQL, MongoDB, Snowflake, and AWS S3, ensuring compliance with PCI DSS, GDPR, AML, and sanctions verification standards.

● Containerized and deployed microservices with Docker, Kubernetes (EKS), Helm, and Terraform (IaC); automated build and release pipelines with GitLab CI/CD and GitHub Actions.

● Enhanced system security with OAuth2, JWT authentication, RBAC, and implemented end-to-end encryption and secrets management (AWS KMS) for compliance-critical workloads.

● Established observability and monitoring using CloudWatch, Prometheus, Grafana, and ELK, enabling proactive alerts and reducing incident response times by 60%.

● Implemented test automation with pytest, unittest.mock, Jest, and React Testing Library, increasing test coverage and ensuring reliability of both backend analyzers and frontend dashboards.

● Collaborated with cross-functional teams (PMs, data scientists, DevOps, QA) in an Agile/Scrum environment, delivering secure and scalable features with strong technical documentation (Swagger/OpenAPI, Postman).