Senior Data Engineer (Python, SQL, AWS)

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 ResponsibilitiesData Pipeline DevelopmentDesign and implement scalable ETL/ELT pipelines for processing vehicle inspection data, images, and metadataBuild real-time data processing workflows for instant inspection results and damage detectionCreate data ingestion solutions from mobile apps, APIs, IoT devices, and third-party automotive systemsImplement data quality frameworks to ensure inspection accuracy and complianceOptimize pipelines for processing high-volume image data and computer vision outputsAWS Data Platform ManagementArchitect data warehousing solutions using Amazon Redshift for vehicle inspection analyticsDesign schemas optimized for automotive data (VIN, inspection history, damage reports, pricing)Implement data lakes using S3 for storing inspection images, videos, and unstructured dataManage inspection metadata and vehicle catalogs using AWS Glue Data CatalogBuild ML-ready datasets for computer vision and damage detection modelsAnalytics & VisualizationDevelop QuickSight dashboards for vehicle inspection metrics, damage trends, and pricing analyticsCreate self-service analytics for dealerships, insurers, and fleet operatorsBuild real-time inspection monitoring dashboards for quality assuranceImplement predictive analytics for vehicle valuation and damage assessmentDesign automated reports for inspection volumes, accuracy rates, and customer KPIsData Integration & OrchestrationIntegrate with automotive data providers (Carfax, KBB, automotive APIs)Build real-time processing for mobile inspection data using KinesisImplement workflows connecting inspection data with customer CRMs and dealer management systemsDesign event-driven architectures for inspection status updates and notificationsCreate APIs for inspection data access by partners and third-party platformsInfrastructure & OperationsImplement Infrastructure as Code using CloudFormation or TerraformSet up monitoring and alerting using CloudWatch and SNSEnsure data security through encryption, VPC configuration, and IAM policiesOptimize AWS costs through resource management and Reserved InstancesMaintain data recovery and backup strategiesOwn 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