With over a decade of experience in Data Engineering, I currently lead a team of data engineers at Porter, where I design and develop large-scale, cloud-native data platforms on GCP and AWS. My work focuses on building reliable, high-performance data infrastructure that powers analytics, experimentation, and business intelligence across the organization. I specialize in architecting modern data platforms from the ground up, designing robust data pipelines, implementing real-time streaming solutions, and optimizing distributed systems for performance and scalability. My technical toolkit spans Spark, Hadoop, Hive, Trino, Iceberg, Kafka, Airflow, Kubernetes, Terraform, and DBT, along with deep experience in AWS and GCP ecosystems. I focus on every stage of the data lifecycle including ingestion, transformation, orchestration, observability, and governance, ensuring that data is consistent, discoverable, and actionable. I have led the development of data platforms and infrastructure components that empower teams to make confident, data-driven decisions at scale. I am also passionate about mentoring aspiring data engineers and helping professionals transition into data engineering roles. Whether it is understanding modern data architectures, learning the right tools, or designing scalable systems, I enjoy simplifying complex concepts and guiding others in building successful careers in this field. If you are looking to discuss data platform architecture, pipeline design, or starting your journey in data engineering, I would be glad to share my experience and help you navigate real-world challenges with practical insights.