Senior Data Engineer with 6+ years of experience designing and optimizing scalable, distributed data platforms for enterprise use cases. I help teams turn complex business requirements into reliable, cost-efficient data systems - from data ingestion and processing to analytics-ready platforms. My work focuses on improving performance, scalability, and infrastructure cost across data pipelines, data lakes, and data warehouses. I have deep hands-on experience with distributed systems (Apache Spark), cloud-native data platforms, and production-grade orchestration. I have worked closely with analytics and data science teams to ensure data systems are robust, observable, and built for scale. Currently, I work as a freelance / consulting Data Engineer, helping organizations identify bottlenecks, reduce compute cost, and design scalable data architectures that hold up in real production environments. Core Expertise: Distributed data platforms & large-scale data processing Data pipeline optimization & cost reduction Data lakes, data warehouses & platform design Cloud-native Data Engineering Technologies: Programming and Data Languages : Python , SQL Big Data : Apache Spark, Pyspark, HDFS, Hive, Apache Druid , Snowflake Orchestration : Airflow, Kubeflow Cloud : AWS S3, EC2, EMR , Lambda, State Machines, Service Catalogue, ECS, Glue, GCP DataProc , GCP Cloud Composer Miscellaneous : Docker , REST APIs , Git