Data Engineer

Highway is the fastest-growing freight tech provider in North America. We serve the largest freight brokers in the industry, solving one of their biggest pain points: who is really hauling their freight. We answer the question of Carrier Identity, protecting brokers’ networks, preventing fraud and increasing transparency. Serving and protecting our customers is our top priority, and we are proud that our best marketing is our customer referrals and testimonials. Role Description Freight brokers put an incredible amount of trust in Highway and that trust will be extended to you. The Data Engineer will be responsible for scaling Highway’s platform in AWS using the best DevOps practices. This role reports directly to the Director of Platform Engineering. Your role: Architect and optimize end-to-end data pipelines that support Highway’s product ecosystems across operational and analytical platforms. Design, implement, and maintain scalable data flow architectures between microservices, AWS Aurora/RDS databases, internal APIs, event-driven systems, and BI tooling. Lead optimization initiatives, including partitioning, indexing, query tuning, retention policies, and performance monitoring for high-volume transactional systems. Define and execute enterprise data warehousing strategies to support reporting, analytics, operational intelligence, and executive decision-making across multiple business domains Support BC/DR strategies to minimize downtime and ensure data resilience. Implement best practices for data security while establishing resilient and highly available data infrastructure leveraging AWS-native services. Implement robust data governance, security, and compliance controls including encryption, access management, auditing, and secure data handling practices aligned with financial and regulatory requirements. Qualifications Proven experience in Data Engineering, Database Engineering, or Backend Platform Engineering with expertise in designing and supporting scalable enterprise data systems. Strong experience with AWS cloud technologies, particularly Aurora/RDS, data architecture, ETL pipelines, microservices, and high-availability distributed systems. Deep knowledge of database optimization and maintenance strategies including indexing, partitioning, query tuning, replication, backup/recovery, and data retention/archival methodologies. Proven ability to implement secure, resilient, and scalable data solutions while adhering to engineering best practices, DevOps principles, CI/CD workflows, and modern data governance standards. Excellent communication skills and comfort working in a fast-paced, changing environment. Key Work Objectives: Architect and Scale Enterprise Data Infrastructure Optimize Database Reliability, Performance, and Retention Enable Data-Driven Operations and Analytics Drive Engineering Excellence and Platform Security #J-18808-Ljbffr