Reddy Naidi

At Tesla, I build telemetry, sensor, and manufacturing data pipelines supporting more than 20 production datasets across Autopilot, Energy, and manufacturing analytics. I've reduced telemetry processing delays by nearly 18%, prepared reusable feature datasets for 10+ predictive maintenance models, and integrated LLM-powered validation to reduce manual anomaly review effort. Previously at Netflix, I processed more than 2 PB of streaming viewership and user-interaction data, reducing ingestion latency by 35% while enabling real-time analytics and personalization. I also built RAG pipelines, lakehouse architecture, MLOps automation, and DataOps capabilities that improved reliability and reduced data-quality incidents. At Intuit, I built ETL and fraud-detection streaming pipelines, modernized warehouse workloads in Snowflake, and supported production ML models for credit risk and customer analytics. I work across Python, SQL, Spark, Kafka, Databricks, AWS, Snowflake, and cloud automation.