Staff Data Engineer
| Company | Atomic Machines |
|---|---|
| Location | Berkeley, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Senior, Expert or higher |
Requirements
- 6+ years (after Bachelor’s) of industry experience.
- Proven experience in data engineering, data flows, and big-data processing.
- Proficiency in Python and programming languages such as SQL.
- Proficiency in data storage solutions (Data Lakes, Cloud Storage, SQL, NoSQL).
- Understanding of manufacturing processes, sensors, and process automation.
- Industry-level experience in guiding and automating data collection and processing in manufacturing environments.
- Knowledge of DevOps practices.
- Strong problem-solving skills and ability to work in a collaborative, fast-paced environment.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, or a related STEM field.
Responsibilities
- Design, build, and maintain scalable data collection, transformation, storage, and integration systems across different manufacturing units and processes.
- Develop data pipelines to process and prepare data for ML model training and real-time analytics.
- Ensure real-time data handling for ML applications and process monitoring.
- Work with inspection engineers/technicians to collect datasets and collaborate with process designers and developers to ensure quality control in manufacturing processes through data validation.
- Guide the creation of validation tests to compare in-house inspection algorithms with commercial tools.
- Establish process monitoring frameworks by creating data storage solutions and implementing structured labeling for process input parameters and associated outputs.
- Develop online statistics and analytics for process control and optimization.
- Analyze observable time-series data corresponding to different manufacturing process stages.
- Derive required datasets, assess data availability, and select appropriate data collection systems to improve data quality and process efficiency.
- Work with process development engineers to propose data collection requirements and communicate those requirements to hardware designers.
- Collaborate with cross-functional teams, including process engineers, chemical engineers, materials scientists, simulation engineers, software developers, data scientists, and ML engineers, to optimize data workflows and improve operational efficiency.
Preferred Qualifications
- Experience with real-time data processing frameworks (Apache Kafka, Spark Streaming, etc.) and with the JMP format.
- Knowledge of ORM and interface abstraction.