Senior Scientific Data Engineer
Leads Scientific Data Engineering team to build data pipelines, schemas, and parsers for pre-clinical lab data using Python/SQL/AI. Architects solutions, mentors juniors, and delivers customer-focused data products with dashboards in React/Streamlit. Requires 8+ years experience.
About the job
Responsibilities
- Lead the Scientific Data Engineering (SDE) Team and build Tetra Data and productizable solutions.
- Work with Product Managers and Solution Architects to understand business requirements and build solutions.
- Take ownership of building data models, prototypes, and integration solutions.
- Use AI agents to build comprehensive data schemas and parsers for pre-clinical data (R&D lab instruments, manufacturing, CRO, CDMO, ELN, LIMS) with formats: .xlsx, .pdf, .txt, .raw, .fid, vendor binaries.
- Extract reusable schema components and parsing functions, productize into Python libraries.
- Build high-quality data pipelines with full unit test and integration test coverage.
- Build data applications, reports, and dashboards using React, Streamlit, Jupyter notebook.
- Collaborate with product managers, project managers, business analysts, data architects, and ML engineers.
- Drive customer value, verify solutions, and act as quality gatekeeper.
- Lead team-wide process/technology improvements and Agile Sprint commitments.
- Provide mentorship to junior SDEs.
Requirements
- 8+ years as Data Engineer or similar.
- 8+ years in Python and SQL focused on data.
- Experience leading projects, managing requirements, timelines, and cross-functional customer implementations.
- Experience with data plotting/dashboarding tools like React and/or Streamlit (strongly preferred).
- Experience with pre-clinical data and lab scientists (strongly preferred).
- Excellent communication, attention to detail, and project delivery leadership.
Benefits
- 100% employer paid benefits for employees and immediate family.
- 401K.
- Unlimited PTO.
- Company paid Life Insurance, LTD/STD.
Skills
Python, SQL, React, Streamlit, Jupyter, AI Agents, Data Pipelines, Unit Testing, Integration Testing, Data Schemas, Data Parsing, Agile, Pre-Clinical Data, Eln, Lims
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