About

Jay Zilpilwar is a GCP certified data engineer with a passion for empowering organizations through data. With a dynamic approach towards the latest technologies like Artificial Intelligence, Machine Learning, Data Science, and Cloud Technologies like Google Cloud and Big Data Stack, he has gained 3.95 years of relevant experience in the field of data engineering. Currently working as a Cloud Data Engineer at KPMG, Jay is responsible for evaluating, developing, maintaining, and testing data engineering solutions for data lake and advanced analytics projects. He also implements processes and logic to extract, transform, and distribute data across one or more data stores from a wide variety of sources. Additionally, he distils business requirements and translates them into technical solutions for data systems, including data warehouses, cubes, marts, lakes, ETL integrations, BI tools, or other components. Jay has also worked as a Data Engineer at Pluto7, where he developed a customer data platform (CDP) data model for one of the clients and built a data pipeline between MongoDB to BigQuery using Fivetran tool. He also used Cloud Function to trigger file-based events and perform ETL using Python code and load data in BigQuery, then used Data Studio for dashboarding. Jay has also worked as an Engineer I at Datametica, where he developed an automatic script that could extract code from the client's database and load it into GCS bucket smoothly. He also found insights from the database warehouse and graph database using Neo4j and Big Query. He loaded data into Data Studio for interactive reports for managers' decisions and for clients' better understanding of their database warehouse patterns. Jay holds a Bachelor of Engineering degree in Computer Engineering from Vishwakarma Institute of Information Technology and a Diploma in Computer Engineering from Government Polytechnic Yavatmal. He has a strong technical skill set that includes Data Engineering, GCP, AWS, SQL, Python, ETL, MongoDB, Big Data, ML, Azure, Integration, Neo4j, Spark, Hadoop, Apache Airflow, Apache Hive, and more.