Relativity Space is building rockets and needs to develop an end-to-end additive manufacturing platform. This role will focus on taking ownership of data architectures and pipelines for process, sensor, robotics, and other data produced during the operation of Relativity's proprietary 3D printing technology, with a critical emphasis on timeseries data.
Requirements
- 7+ years experience in the field of data engineering, including time spent owning or leading data infrastructure projects
- Strong programming skills in Python and SQL and familiarity with other programming languages
- Experience working in a Linux or Unix-based (CLI) development environment and deploying to cloud, local, or hybrid compute infrastructure
- Experience with message protocols for timeseries and telemetry data streaming
- Expertise in designing, querying, and maintaining relational and timeseries databases
- Experience building and maintaining scalable, resilient data pipelines (ETL) for machine learning workflows, including data validation, transformation, labeling, and versioning
- Experience working with scientific timeseries data from systems such as high-frequency electronics, sensors, audio, video, or robotics
Responsibilities
- Take ownership of data architectures and pipelines for process, sensor, robotics, and other data that are produced during the operation of Relativity's proprietary 3D printing technology, with a critical emphasis on timeseries data.
- Developing database structures and schemas
- Working with communication protocols
- Maintaining data collection, processing, and analysis pipelines
- Gathering requirements and evaluate the existing data infrastructure
- Identify where it makes sense to solidify existing approaches and where it makes sense to create new solutions
- Ensuring that data are ready to be read into model training pipelines and assisting with data solutions for model repositories and inference data
Other
- Bachelor's degree in Computer Science, Engineering, or related field
- Communicate planning, progress, risks, and blockers with other teams and leadership
- Able to describe blockers and resource needs to a variety of stakeholders
- Experience in the field of additive manufacturing
- Proficiency with univariate statistics
