We need smart, ambitious R & D engineers to help extend and leverage our powerful time-series database. You will build new features and capabilities on top of our database, develop connectors or integrations with other analytical, storage, and visualization systems, and provide tooling and systems for managing and deploying TimescaleDB in various environments. You are a technical generalist who enjoys the challenge and flexibility of many different projects.
This is a full time position at our office in New York City or Stockholm.
- Develop new features and functions for TimescaleDB to improve its usability and capabilities.
- Build, test, and document reference architectures for integrating TimescaleDB into and across a variety of software environments.
- Release tools and systems for managing and operating TimescaleDB in a variety of settings: edge, on premise, cloud.
- Continually improve the database’s reliability and performance through testing and benchmarking.
- Document best practices for deploying and integrating TimescaleDB for our users.
- Provide technical assistance to high-value customers, using that to gain insight into the needs and experiences of our users.
- Be an enthusiastic and personable teammate, receiving and providing code reviews, and otherwise partnering and helping other engineers.
- Bachelor’s degree in computer science or equivalent.
- 2 + years engineering experience.
- Data engineering and backend generalist, comfortable across many systems, frameworks, languages.
- Interested in testing various deployment models and hardware configurations (from cloud to IoT gateways); exploring RAID, ZKS, NVMe, and network-attached disk setups; determining feasibility with other in-database extensions; and more.
- Operational experience with databases and PostgreSQL (in particular) highly desirable.
- Experience programming in SQL, Go, Python, C/C++, or shell scripting.
- Experience with testing frameworks, benchmarking, CI/CD tools, and release engineering desirable.
- Familiarity with a variety of data processing, streaming, and storage systems, as well as data connectors and integrations between them.
- Comfortable with both quick and dirty prototyping, as well as writing well tested and documented code for release.
- Passionate about solving complex data and infrastructure problems.