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Sr. Mission Operations Software Engineer
| Company | Tomorrow.io |
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| Location | Golden, CO, USA |
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| Salary | $130000 – $160000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s |
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| Experience Level | Senior |
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Requirements
- 6+ years of experience building production software
- B.S. in Computer Science, Aerospace Engineering, or related field
- Ability to work autonomously/independently on complex projects
- Work with stakeholders to clarify requirements and satisfy product needs
- Experience developing fault-tolerant production-quality software
- Understanding of distributed systems architecture
- Advanced knowledge of Python (4+ years)
- REST API design, implementation and frameworks (aiohttp, Flask, etc.)
- Data modeling (Data Classes, Enumerations, Type Hinting)
- Database interfaces (SQLAlchemy, PyMongo, InfluxDB)
- Communication protocols (namedtuple, struct, socket)
- Quality assurance (pytest, mocker, PEP 8)
- Platforms/Infrastructure: AWS (Elastic Container Service, Lambda, S3, SQS), Terraform
- Intermediate knowledge of Docker and Kubernetes
- Intermediate knowledge of SQL, NoSQL, and/or time series databases
- Intermediate knowledge of GCP, Azure resources
Responsibilities
- Develop the tools mission operators and climate scientists need to achieve mission success
- Support payload operators and scientists in achieving mission success
- Contribute to the definition of interfaces between various components (ground system to spacecraft, spacecraft bus to payload, etc.)
- Work with DevOps and IT teams on topics such as production environment, deployment strategies, and security measures
- Provide training and documentation for all production software systems
- Provide mentoring to more junior engineers as needed
Preferred Qualifications
- Argo Workflows/Events
- Async I/O (asyncio, aiohttp)
- C/C++ experience
- Exposure to aerospace systems (i.e. satellites, airplanes, rockets)
- Exposure to satellite telemetry data processing (e.g., CCSDS)
- Exposure to satellite mission planning and resource deconfliction
- Scientific computing (NumPy/SciPy, Pandas, Matplotlib)
- Web applications: React, HTML, CSS, and JavaScript; Modern JavaScript frameworks (Angular, React.js, Vue.js); Communication protocols (WebSocket, Socket.IO, JSON)
- Data visualization: Visualization platforms (Grafana, DataDog, Plotly Dash); Graphics and plotting libraries (Plotly, SVG, Canvas, WebGL, D3.js, Three.js)
