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.
What You'll Do
- 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.
What We're Looking For
This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.
This is NOT a fully remote position!
- 4-6 years of experience as a Data Engineer, Backend Engineer, Database Engineer, or similar role.
- Strong programming experience in Python, C++, Golang, or similar languages.
- Experience building and operating real-time and batch data pipelines in production environments.
- Deep expertise with PostgreSQL, including performance tuning, indexing, partitioning, and schema design.
- Experience with NoSQL, in-memory databases, and large-scale data processing systems.
- Strong communication skills and the ability to collaborate across engineering, analytics, product, and infrastructure teams.
Someone Who Will Thrive in This Role
- Thinks like a platform engineer and enjoys building tools that make other engineers more effective.
- Likes designing systems that will grow with the company over many years rather than simply solving today's problem.
- Enjoys working behind the scenes to enable AI, autonomy, and engineering teams.
- Takes ownership of systems from design through production operations.
- Values data quality, reliability, and observability.
- Collaborates effectively with both technical and non-technical stakeholders.
- Balances long-term platform thinking with practical delivery needs.
- Enjoys exploring databases, distributed systems, analytics, or data-intensive side projects.
Bonus Points
- Experience with Kafka, Redpanda, RabbitMQ, Pulsar, or other streaming technologies.
- Experience with AWS or cloud-based data platforms.
- Experience with S3, Parquet, ORC, Delta Lake, or modern data lake architectures.
- Experience with orchestration tools such as Airflow, Dagster, or Prefect.
- Knowledge of distributed systems, caching, replication, sharding, and high-availability database design.
At MatrixSpace, Data Engineering is where critical information becomes actionable insight. This isn't a role focused on maintaining legacy systems or reacting to operational issues. Instead, you'll help lay the technical foundation that allows MatrixSpace to collect, organize, and learn from massive amounts of sensor data for years to come.
Skills Required
- 4-6 years of experience as a Data Engineer, Backend Engineer, Database Engineer, or similar role.
- Strong programming experience in Python, C++, or Golang.
- Experience building and operating real-time and batch data pipelines in production.
- Deep expertise with PostgreSQL including performance tuning, indexing, partitioning, and schema design.
- Experience with NoSQL, in-memory databases, and large-scale data processing systems.
- Strong communication skills and ability to collaborate across engineering, analytics, product, and infrastructure teams.
- Must be legally authorized to work in the United States without employer sponsorship.
- Position is not fully remote (on-site or not fully remote work required).
- May be required to obtain and maintain a U.S. government security clearance in the future.
- Experience with streaming technologies such as Kafka, Redpanda, RabbitMQ, or Pulsar.
- Experience with AWS or other cloud-based data platforms.
- Experience with S3, Parquet, ORC, Delta Lake, or modern data lake architectures.
- Experience with orchestration tools like Airflow, Dagster, or Prefect.
- Knowledge of distributed systems, caching, replication, sharding, and high-availability database design.
What We Do
We're a technology leader in Autonomous Flight Systems. Our products fly themselves, incorporate cutting edge AI, and sense what's around them. This is a place for people that have the intellectual talent and tenacity to invent new things and get them to work. It's demanding but a lot of fun.
Why Work With Us
Our culture is for innovators who want to build real systems and see them work. Our team of engineers and scientists come from many different disciplines, and our technology is truly cutting edge. This is an elite team for the curious, talented, and hard working professionals that want to make history with their products.
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