Senior Scientific Data Engineer

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.