About

Durgesh Pandey is a skilled Data Engineer and Big Data Developer with over 2.5 years of experience in the field. He has a strong background in Data Engineering, and is actively involved in the development of Data-centered and BI Applications. Durgesh has a proven track record of taking projects from the imagination phase all the way to production, including requirement gathering, development, UAT, and deployment. Durgesh is highly skilled in distributed processing of Data, and has a deep understanding of the Hadoop ecosystem. He is also knowledgeable in Data warehousing and ETL Development. Durgesh has a good grasp of Computer Science Fundamentals and Programming, which allows him to approach problems from multiple angles. Durgesh is currently learning Databricks, Deltalake, and Delta Live Tables to expand his skillset even further. He has contributed to research spikes to determine the feasibility of solutions by creating and presenting POCs. Durgesh is a quick learner and always eager to take on new challenges. Durgesh is currently working as a Data Engineer at Grab, where he is utilizing his skills to contribute to the development of various projects. Prior to this, he worked as an Associate Consultant and Senior Analyst at Capgemini. In his role at Capgemini, he worked on a Supply Chain project for a client, where he built Data Quality Rules to determine the overall quality of Business Data and presented it in the form of a Data Quality Score dashboard. He also worked on a part of the project to reduce the gap in supply/demand/inventory to reduce the cost by using excess inventory materials. Durgesh holds a Bachelor's degree in Computer Science from Chandigarh University. He is proficient in various technologies such as Data Engineering, Big Data, SQL, ETL, Databricks, Python, Azure, Research Scientist, Hadoop, Apache Hive, Spark, Snowflake, Data Warehouse, CI/CD, and Software Engineering. Durgesh's relevant experience in the field is 2.77 years, and he is always looking to expand his knowledge and skills in the field of Data Engineering and Big Data.