Senior Engineer - Lead Developer Data Analytics

Built and maintained large-scale data pipelines using Python, PySpark, and AWS services (S3, Athena, EC2, SQS) for sensor data analysis from Camera, LiDAR, and GPS modules.

Maintained and extended the backend of KPI tooling systems using Node.js and MongoDB to support validation workflows and visualization.

Designed relational SQL schemas for structured storage of perception test data and KPI results.

Automated test execution, report generation, and feature validation, reducing manual overhead by 50%.

Created interactive dashboards using AWS Quicksight and Plotly to support data-driven decisions for ADAS validation teams.

Implemented and retrained the YOLOv7 deep learning model to detect custom object types for test automation and KPI generation in vision-based ADAS functions.

Led a team of 4–5 developers, reviewed code, and coordinated task planning with OEM partners and internal teams.

KPI Tooling: Designed modular backend APIs in Node.js and MongoDB; enabled dashboard visualizations and AWS based data processing.

Audi – Multi-Functional Front Camera: KPI design for object detection, pedestrian/lane/traffic sign recognition; root cause analysis, outlier identification.

VW – Trained Park Assist: KPI generation and ground truth derivation using DGPS/IPS data in complex parking scenarios.

BMW – LiDAR Validation: Point cloud analysis for false-positive/negative detection, safety related scenario analysis.