Data Engineer (Python, SQL, AWS)

About Pave.aiPAVE is changing the way the world inspects vehicles. Our virtual inspection platform transforms anyone, anytime, anywhere, into a professional inspector. We are committed to continuous innovation by digitizing and automating vehicle inspections to enable trustworthy and transparent decision-making for the automotive industry. Through cutting-edge AI and computer vision technology, we're building the future of vehicle inspection and automotive commerce. Position OverviewWe’re looking for a talented Data Engineer with strong AWS expertise to design, build, and maintain the data infrastructure that powers our vehicle inspection platform. At Pave.ai, you’ll be responsible for developing scalable and reliable data pipelines that process millions of vehicle inspections, images, and automotive data points — delivering real-time insights to customers across the automotive ecosystem.In this role, you will collaborate closely with our engineering and data science teams based in both Canada and Vietnam, working together to design end-to-end solutions that support advanced analytics, machine learning models, and business intelligence tools. You’ll play a key role in ensuring data accuracy, scalability, and system performance. Key Responsibilities Data Pipeline Development Design and implement scalable ETL/ELT pipelines for processing vehicle inspection data, images, and metadata Build real-time data processing workflows for instant inspection results and damage detection Create data ingestion solutions from mobile apps, APIs, IoT devices, and third-party automotive systems Implement data quality frameworks to ensure inspection accuracy and compliance Optimize pipelines for processing high-volume image data and computer vision outputs AWS Data Platform Management Architect data warehousing solutions using Amazon Redshift for vehicle inspection analytics Design schemas optimized for automotive data (VIN, inspection history, damage reports, pricing) Implement data lakes using S3 for storing inspection images, videos, and unstructured data Manage inspection metadata and vehicle catalogs using AWS Glue Data Catalog Build ML-ready datasets for computer vision and damage detection models Analytics & Visualization Develop QuickSight dashboards for vehicle inspection metrics, damage trends, and pricing analytics Create self-service analytics for dealerships, insurers, and fleet operators Build real-time inspection monitoring dashboards for quality assurance Implement predictive analytics for vehicle valuation and damage assessment Design automated reports for inspection volumes, accuracy rates, and customer KPIs Data Integration & Orchestration Integrate with automotive data providers (Carfax, KBB, automotive APIs) Build real-time processing for mobile inspection data using Kinesis Implement workflows connecting inspection data with customer CRMs and dealer management systems Design event-driven architectures for inspection status updates and notifications Create APIs for inspection data access by partners and third-party platforms Infrastructure & Operations Implement Infrastructure as Code using CloudFormation or Terraform Set up monitoring and alerting using CloudWatch and SNS Ensure data security through encryption, VPC configuration, and IAM policies Optimize AWS costs through resource management and Reserved Instances Maintain data recovery and backup strategies Own operational reliability of the data platform, including versioned pipelines, CI/CD integration for test data provisioning, and improvements in data quality and governance to prevent application failures from raw vs. processed data mismatches