CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats.
CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.
Role Overview
Data is foundational to how CHAOS develops, tests, and improves complex sensing systems. As the company scales, we need a data operating model that makes information consistent, trusted, secure, and usable across Engineering, AI, Test, and business teams.
As Manager of Data Management and Operations, you'll own the end-to-end data lifecycle: how data is defined, collected, transported, governed, transformed, secured, and delivered for analysis. You'll lead our data management and field data operations functions, partnering closely with the Foundry engineering team to ensure the platform meets company needs.
This isn't an analytics-only role. It's a technical and operational leadership role spanning data governance, data-platform coordination, and test operations. You'll build durable systems and teams while remaining close enough to field execution to understand where data quality and collection break down.
Success means teams use the same definitions, analysts can trust the datasets they receive, test data is captured and available quickly, and access to sensitive data is controlled and auditable without becoming a barrier to execution.
Responsibilities
- Establish company-wide governance for data definitions, ownership, quality, lineage, retention, and calculation change management.
- Create authoritative, documented analytical datasets and shared definitions so teams can work from consistent data and metrics.
- Work with the Foundry engineering team to ensure that data ingestion, ETL, modeling, transformation, validation, and monitoring align with stakeholder needs.
- Own permissions management and partner with Security and Compliance to implement least-privilege access, auditability, retention, and handling controls for sensitive data.
- Build a repeatable process for planning data capture at test events, including required sensor data, metadata, truth data, labels, logging, storage, and validation.
