RUPENDRA LANKE

• 4 years of experience as a Data Engineer building robust data pipelines for large-scale structured and unstructured datasets. Expertise in data acquisition, validation, modeling (predictive, statistical, and data), and visualization, driving actionable insights • Ability to develop efficient dimensional models in Snowflake, optimizing query performance for various data analysis scenarios. • Processed and transformed large datasets (petabytes/terabytes) on Databricks using Spark SQL and Spark DataFrames, enabling advanced data analytics for projects with users. • Experience in RDBMS concepts, Data Modeling (Facts and Dimensions, Star/Snowflake schemes), Data Migration, Data Cleansing and ETL Processes. • Engineered enterprise solutions by employing batch processing with DataBricks and integrating streaming frameworks, including Spark Streaming, Apache Kafka, and Apache Airflow. • Excellent knowledge of AWS cloud services, including EC2, S3 Bucket, Amazon Redshift, Glue, Lambda, and Athena, with expertise in infrastructure management, storage, data warehousing, serverless computing, and automated deployment.