Data Engineer

Help build the data infrastructure that enables MatrixSpace to continuously learn from real-world radar deployments.

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them.

By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.

We're looking for a hands-on Data Engineer to design, build, and optimize the data infrastructure that powers our internal engineering workflows.

You'll build scalable pipelines that ingest and organize data collected from MatrixSpace systems deployed in the field, enabling our engineering teams to improve AI algorithms, develop new sensing capabilities, and build the next generation of our platform.

You'll work closely with engineering, product, and infrastructure teams to ensure data is accurate, performant, and accessible.

If you're analytical, detail-oriented, and passionate about building robust data systems at scale, we'd love to talk.

• Design the internal data platform that enables engineering teams to ingest, organize, and analyze data collected from deployed radar systems.
• Build the internal data platform that enables engineering teams to ingest, organize, and learn from data collected by MatrixSpace systems in the field.
• Build data ingestion, transformation, enrichment, aggregation, and publishing workflows.
• Develop solutions across relational, NoSQL, in-memory, time-series, warehouse, and data lake technologies.
• Optimize PostgreSQL databases through schema design, indexing, partitioning, and query tuning.
• Implement advanced analytics, aggregation, and statistical processing across large datasets.
• Monitor pipeline reliability, performance, data quality, and system observability.

This position requires working directly or indirectly with the US Government in restricted environments.