Software Engineer 2
About The Position
Design, build, and own large-scale backend services supporting high-volume data ingestion, tagging, transformation, querying, and downloading across enterprise data platforms. Develop API-driven backend services and REST interfaces for cloud-based workflows, vehicle testing systems, data visualization tools, and enterprise data access, enabling reliable data access, workflow automation, and consistent data governance across teams. Implement core data-management capabilities, including access-control enforcement, schema validation, caching strategies, partitioning logic, and intelligent file placement to optimize performance and cost. Design, implement, and maintain end-to-end data workflows that track data from initial truck-side ingestion through processing, annotation, storage, and downstream consumption. Architect and manage cloud-based foundations for backend and data platforms using AWS services for scalable storage, compute orchestration, and production environment configuration. Build product-level metrics, schemas, dashboards, and visualizations using internal metric pipelines, post-processing frameworks, and Tableau. Lead architecture discussions and define system interfaces, data models, and integration patterns for cross-team platforms. Deliver cost-saving initiatives through intelligent data lifecycle management and S3 storage tiering strategies. Participate in roadmap planning, multi-team architecture reviews, and long-term system strategy. Mentor engineers and interns, guide complex feature implementation, and support onboarding to backend systems and data workflows. Improve service reliability by triaging and resolving operational alerts with Datadog and internal debugging tools, and contribute to automating on-call scheduling processes. The position is located at the Blacksburg HQ and is eligible to be performed from anywhere in the U.S.
Requirements
- Master's degree in Computer Engineering, Computer Science, or a related technical field, plus 2 years of industry experience as a Software Engineer or in a related occupation building cloud-based systems on AWS; alternatively, a bachelor's degree in one of these fields plus 5 years of professional experience in such a role.
- Experience designing AWS cloud-native architectures using Lambda, Step Functions, IAM, S3, and EC2.
- Experience building high-throughput ETL/ELT pipelines for reliable, large-scale data processing.
- Experience in Python backend engineering and developing cloud-based services with REST API design.
- Experience with Infrastructure as Code and DevOps automation using Terraform, GitHub Actions, and CI/CD pipelines.
- Experience deploying scalable backend services using Docker, ECR, and ECS.
- Experience with data modeling, data workflows, and data quality/governance for distributed applications.
- Experience building monitoring and metric/KPI dashboards, alert pipelines, and failure-handling workflows using Datadog, PagerDuty, and Tableau.
Responsibilities
- Design, build, and own large-scale backend services for high-volume data ingestion, tagging, transformation, querying, and downloading.
- Develop API-driven backend services and REST interfaces for cloud workflows, vehicle testing systems, visualization tools, and enterprise data access.
- Implement data-management capabilities such as access control, schema validation, caching, partitioning, and intelligent file placement.
- Design and maintain end-to-end data workflows from truck-side ingestion through processing, annotation, storage, and downstream consumption.
- Architect and manage AWS-based backend and data platform foundations for scalable storage, compute orchestration, and production environments.
- Build product metrics, schemas, dashboards, and visualizations using internal metric pipelines, post-processing frameworks, and Tableau.
- Lead architecture discussions and define system interfaces, data models, and integration patterns across teams.
- Implement data lifecycle management and S3 storage tiering strategies to reduce costs.
- Participate in roadmap planning, architecture reviews, and long-term system strategy.
- Mentor engineers and interns, guide complex feature implementation, and support onboarding.
- Triage and resolve operational alerts using Datadog and internal debugging tools, and contribute to on-call scheduling automation.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
