VIA is making an impact, and so can you.
Headquartered in Boston, VIA provides mission-critical software for secure data exchange and trustworthy AI without compromising speed, simplicity, or resilience. Its military-grade architecture helps defense, public safety agencies, and humanitarian organizations use AI while maintaining control of sensitive, distributed data even in contested or offline environments.
Learn more: solvewithvia.com .
An impressive mission requires an equally impressive Senior Data Platform Engineer.
As a Senior Data Platform Engineer at VIA, you'll bring together core data engineering skills with an interest in the DevOps side of things: Kubernetes, container insights, and resource allocation, alongside a solid understanding of our application logic, database queries, and data pipeline orchestration. Your day-to-day will include supporting application workflows and pipeline reliability, and helping us stay ahead of the scaling and observability challenges that come with growth.
You will build the foundation that empowers our customers to harness AI for human-centric, data-driven decision-making. You will work cross-functionally with a high-performing team of data professionals, developers, DevOps, and Client Delivery specialists who are already pushing the boundaries of what's possible with AI.
Individuals who excel in this role are motivated by solving complex data infrastructure and reliability challenges, holding a high bar for pipeline observability and system performance, and enjoy operating at the intersection of application logic and infrastructure. Are you ready to join us?
Read more about our mission, team, and values here.
In this role, you will:
Architect & provision secure data infrastructure: Design, provision, and maintain cloud-based data storage and platform infrastructure using infrastructure-as-code (e.g., Terraform, Helm), optimizing schemas for multi-tenant environments while ensuring security and a high standard of trust and transparency
Engineer and deploy data pipelines: Develop, deploy, and maintain resilient pipelines for both real-time streaming and batch processing, with deployment (CI/CD, IaC) as a top priority, ensuring seamless data flow from raw ingestion to production-ready applications
Monitor and optimize infrastructure: Build monitoring and alerting systems to track data health and system performance, proactively identifying and remediating bottlenecks
Support application workflows: Partner directly with the application team to troubleshoot database queries, pipeline logic, and data-related application issues as they come up
Drive data governance and best practices: Contribute across teams to recommend tools, processes, and best practices for maintaining data health, integrity, and security
Operationalize AI models: Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models
Requirements
What you will bring to this role:
Experience: 5+ years of experience in a data-driven role
Education: Bachelor’s or Master's degree in science, mathematics, engineering, or a data-driven field
Core engineering: A strong foundation in Python (or equivalent) for scripting, automation, and tooling across the data platform
Data architecture: Proven experience architecting scalable relational and non-relational (SQL/NoSQL) schemas
Performance engineering: Expertise in maximizing system performance through advanced query tuning, strategic indexing, and execution plan analysis to eliminate technical bottlenecks
Cloud & platform infrastructure: Hands-on experience with AWS data services (e.g., RDS, Aurora, Lambda) or Azure equivalents, plus infrastructure-as-code (Terraform and/or Helm) for provisioning and deploying data infrastructure
Container orchestration & monitoring: Working knowledge of container build and orchestration tools (e.g., Kubernetes, Docker), and container-level observability (e.g., resource allocation, cluster health, container…