I am a Senior Azure Data Engineer with over 12 years of experience delivering enterprise-scale data platforms across diverse industries such as Banking, Healthcare, Pharma, Insurance, and Asset Management. My expertise lies in supporting regulated analytics, fraud detection, risk modeling, and high-volume transactional systems. I take ownership of the full software development lifecycle, including requirements analysis, solution design, distributed data engineering, validation frameworks, performance optimization, and controlled Dev/QA/Prod releases.
I have deep expertise in Microsoft Fabric technologies, designing modern Medallion architectures for enterprise migration and modernization initiatives. I am skilled in building scalable Lakehouse architectures using Azure Databricks and ADLS Gen2, with a strong command of Delta Lake internals and Delta Live Tables for managing ACID guarantees and data lifecycle controls.
My experience extends to implementing governance and security using Azure AD, Apache Ranger, AWS Lake Formation, and encryption standards aligned with regulatory compliance such as HIPAA, SOX, PCI-DSS, Basel III, SEC, and GxP. I am proficient in designing ingestion and streaming architectures using Azure Data Factory, Event Hubs, Kafka, and Informatica PowerCenter.
I have a strong background in performance engineering across Spark, Fabric, Synapse, and Snowflake, optimizing shuffle behavior, partition strategies, and compute capacity utilization. Additionally, I prepare ML-ready datasets using Databricks Feature Store, MLflow, and Azure Machine Learning to enable predictive analytics.
I am experienced in CI/CD and infrastructure automation using Azure DevOps, GitHub Actions, Jenkins, Terraform, ARM/Bicep, Docker, and Kubernetes, supporting scalable multi-environment deployments. Throughout my career, I have collaborated closely with business, analytics, compliance, and risk management stakeholders to deliver scalable, governed, and compliant data solutions.
I am passionate about guiding data engineering teams on Azure Lakehouse design patterns and continuously improving data platform performance and governance to meet evolving enterprise needs.