About

Prathamesh Naidu is an experienced Data Engineer with over 5 years of experience in designing and implementing ETL/Data Pipelines for analytics stakeholders. He is currently working as a Data Engineer II at Expedia Group, where he has designed and developed data/ETL pipelines and workflows for various metrics for BI & Product Analytics stakeholders using SQL, Python, PySpark, SparkSQL, AWS S3, Airflow, Qubole, Trino, and Databricks for cohort analysis, experimentation, product performance, and data reporting. He has also led the migration of existing ETL pipelines from Qubole Presto workflows to a combination of SQL, PySpark, Trino, and SparkSQL implementation using Jupyter/Databricks Notebooks and Airflow that resulted in a reduction of ETL processing time by 35%. Prathamesh is skilled in various Data Engineering technologies like SQL, Python, Spark, Airflow, Hive, Trino/Presto, Git, CICD, and Data Engineering methodologies like Data/Dimensional Modelling, Star/Snowflake Schema, ETL, Incremental Loads, Slowly Changing Dimensions. He is very dedicated, a quick learner, and eager to learn new tools and technologies. His role involves interaction with stakeholders on a day-to-day basis to understand their requirements, use cases, and the scope of the analytics solutions like how is the data going to be consumed. During his tenure, he has also led teams consisting of 3-5 developers where he was responsible for project planning, delivery, and execution, and was accountable for all the work done by the team. He has some additional experience in the BI space where he has built several dashboards using tools like QlikSense and Tableau. Prathamesh has a Bachelor of Technology (B.Tech.) degree in Computer Science from Symbiosis and has completed his high school education from Fiitjee and Kendriya Vidyalaya. He is skilled in various technologies like SQL, Data Engineering, Apache Airflow, ETL, Python, Databricks, Big Data, AWS, Jupyter, Senior Software Engineer, Snowflake, Data Warehouse, Spark, Jenkins, Infra, Apache Hive, NoSQL, Test, GCP, Amazon Athena, MySQL, Cassandra, Hadoop, and Mobile.