Yuvraj Singh Tomar

• Designed and developed PySpark ETL pipelines to process connected vehicle telemetry data

• Worked with Honda engineering teams to process and transform large-scale connected vehicle telemetry data using PySpark, Kafka, AWS EMR and Snowflake

• Implemented Bronze (JSON), Silver (Parquet) and Gold (business-ready) data architecture on Amazon S3

• Worked with Kafka for streaming ingestion and Spark on AWS EMR for distributed processing

• Developed curated analytical datasets that were consumed by downstream analytics and data science teams for model training, validation, and predictive analysis. Collaborated with business stakeholders to ensure the datasets met reporting and analytical requirements

• Developed a robust source-to-target validation framework using SQL and PySpark to ensure data completeness, consistency, and integrity across Bronze, Silver, and Gold layers, achieving over 99.9% validation accuracy before business consumption

• Worked with AWS IAM roles for secure integration between Amazon S3 and Snowflake

• Collaborated with Business, QA and Analytics teams to deliver production-ready datasets

• Built scripts for data extraction and transformation
• Worked with Spark on AWS EMR within the Hadoop ecosystem

• Provided production support, root cause analysis and ETL enhancements

• Led a team of 5 engineers for approximately 3 months

• Automated repetitive tasks using Python & shell scripting, improving efficiency
• Developed ETL pipelines using Python and PySpark to transform large-scale automotive radar log data from Linux environments into structured CSV and tabular formats for analysis and validation
• Performed log analysis and data validation for system testing
• Supported performance testing and debugging of applications
• Closely worked with QA and product teams to implement features, track bugs, and deliver regular updates to stakeholders