About
I have 10+ years of experience designing and delivering enterprise-grade solutions using Python, PL/SQL, and advanced ETL frameworks across finance, healthcare, and telecom domains, with extensive experience working in remote and distributed team environments. My expertise spans data engineering, automation, microservices architecture, and cloud-native deployments using Django, Flask, FastAPI, Airflow, Snowflake, Neo4j, Kafka, and advanced SQL tuning to build scalable, high-performance data platforms.
I specialize in building hybrid data pipelines and analytics ecosystems integrating Python, Pandas, NumPy, Great Expectations, Informatica, Databricks, and SQL Loader, enabling reliable data ingestion, reconciliation, validation, and reporting across AWS, Azure, and GCP. I design containerized microservices using Docker, Kubernetes, Helm, and implement CI/CD pipelines with Jenkins, GitHub Actions, Azure DevOps, and Cloud Build to support seamless, automated deployments in remote-first delivery models.
I have strong experience in cloud architecture, monitoring, and observability using Grafana, ELK, Prometheus, CloudWatch, and Stackdriver, along with implementing secure authentication using OAuth2, JWT, IAM, RBAC, and CyberArk. I collaborate effectively with cross-functional teams across time zones, following Agile, SDLC, and DevOps best practices to deliver reliable, secure, and high-quality solutions in fully remote settings.
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