We are seeking a Scientific Data Engineer to join our team.
Responsibilities:
- Own, prototype, and implement customer solutions.
- Research and prototype data acquisition strategy for scientific lab instrumentation.
- Research and prototype file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries).
- Design and build data models.
- Design and build Python data pipelines, unit tests, integration tests, and utility functions.
- Build visualization, report, and dashboards using Spotfire, Tableau, Jupyter notebook and etc.
- Work with the customer to test and make sure the solution fulfills their requirements and solves their need.
- Coordinate project kickoff meetings; manage the customer relationship throughout the project, and conduct formal project closeout meetings.
- Facilitate internal project post-mortems to identify areas of improvement on the next implementation.
Requirements:
- 7+ Sr. Engineer.
- Python (Pandas/Numpy).
- ETL.
- Relational Databases / SQL.
- Message Oriented Systems.
- Databricks (ETL Tools).
- Passionate about science and building solutions to make the data more accessible to end-users.
- Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
- Quickly understand a highly technical product and effectively communicate with product management and engineering.
- Proactive problem-solving skills.
- High-bandwidth: thrives when managing multiple simultaneous projects.
- Intellectually curious unwavering drive to learn more every day.
- Ability to think creatively about how to solve projects risks without reducing quality.
- Team player and ability to 'roll up your sleeves' and do what it takes to make the team succcesful.
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