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Salary: USD 145,000 - 190,000 / annual
VIA is a mission-critical software company enabling organizations to share and analyze sensitive data securely. The company serves the Department of War, Fortune 50 companies, and critical infrastructure organizations globally, combining decentralized architecture, agentic AI, and military-grade security to make sensitive data usable in any environment, including offline settings.
As a Senior Data Platform Engineer, you will architect and operate the data infrastructure that powers VIA's analytics and AI capabilities. You'll work at the intersection of data engineering and DevOps, designing secure, scalable cloud-based data platforms while ensuring reliability, observability, and performance at scale.
Key responsibilities include:
- Architect and provision secure, multi-tenant data infrastructure using infrastructure-as-code (Terraform, Helm)
- Design and optimize relational and non-relational database schemas for performance and security
- Engineer resilient data pipelines for real-time streaming and batch processing with CI/CD as a priority
- Build comprehensive monitoring and alerting systems to track data health and system performance
- Partner with application teams to troubleshoot database queries, pipeline logic, and data-related issues
- Contribute to data governance, recommending tools and best practices across teams
- Support MLOps by managing versioning, containerization, and deployment of AI models
- Optimize system performance through query tuning, strategic indexing, and execution plan analysis
You'll collaborate cross-functionally with data professionals, developers, DevOps engineers, and Client Delivery specialists on complex infrastructure and reliability challenges.
Requirements:
- 5+ years of experience in a data-driven role
- Bachelor's or Master's degree in science, mathematics, engineering, or related field
- Strong Python proficiency for scripting, automation, and tooling
- Proven experience architecting scalable SQL and NoSQL schemas
- Expertise in query tuning, strategic indexing, and execution plan analysis
- Hands-on experience with AWS data services (RDS, Aurora, Lambda) or Azure equivalents
- Proficiency with infrastructure-as-code (Terraform and/or Helm)
- Working knowledge of Kubernetes, Docker, and container-level observability
- Experience building resilient pipelines with Dagster or Apache Airflow
- Strong understanding of data infrastructure integration within broader application architecture
- Demonstrated experience with Git, CI/CD pipelines, and production system deployment
