Mô tả công việc
Position Overview
We’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
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
Build real- time data processing workflows for instant inspection results and damage detection
Design and implement scalable ETL/ELT pipelines for processing vehicle inspection data, images, and metadata
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
Implement data lakes using S3 for storing inspection images, videos, and unstructured data
Design schemas optimized for automotive data (VIN, inspection history, damage reports, pricing)
Build ML- ready datasets for computer vision and damage detection models
Manage inspection metadata and vehicle catalogs using AWS Glue Data Catalog
Analytics & Visualization
Design automated reports for inspection volumes, accuracy rates, and customer KPIs
Create self- service analytics for dealerships, insurers, and fleet operators
Implement predictive analytics for vehicle valuation and damage assessment
Build real- time inspection monitoring dashboards for quality assurance
Develop QuickSight dashboards for vehicle inspection metrics, damage trends, and pricing analytics
Data Integration & Orchestration
Implement workflows connecting inspection data with customer CRMs and dealer management systems
Integrate with automotive data providers (Carfax, KBB, automotive APIs)
Build real- time processing for mobile inspection data using Kinesis
Design event- driven architectures for inspection status updates and notifications
Create APIs for inspection data access by partners and third- party platforms
Infrastructure & Operations
Ensure data security through encryption, VPC configuration, and IAM policies
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
Optimize AWS costs through resource management and Reserved Instances
Set up monitoring and alerting using CloudWatch and SNS
Implement Infrastructure as Code using CloudFormation or Terraform
