Senior Scientific Engineer; Remote

Join Tetra Science , the Scientific Data and AI Company behind Tetra OS , an operating system for scientific intelligence that helps leading life sciences organizations transform fragmented scientific data into AI-native assets and workflows. This is a full-time Senior Scientific Data Engineer opportunity focused on scientific data engineering, AI-enabled data processing, Python development, and large-scale data integration solutions.
Location: [Confirm: location/work arrangement needed] .

This is an opportunity to lead a highly visible Scientific Data Engineering team and help build the foundation of Tetra Science's data engineering platform. The ideal candidate thrives in a fast-paced environment, enjoys mentoring engineers, partnering with product and solution teams, and delivering mission-critical customer solutions. You'll work at the intersection of scientific data, AI, cloud-scale data engineering, and life sciences innovation while influencing architecture, quality standards, and team growth.

• 8 years of experience building data products as a Data Engineer or related professional
• 8 years of hands-on experience with Python and SQL focused on data engineering
• Experience leading projects, gathering requirements, and managing timelines
• Experience managing multiple customer-focused implementation projects across cross-functional teams
• Experience building sustainable delivery processes and managing project milestones
• Strong communication skills and attention to detail
• Ability to quickly understand complex technical products and collaborate effectively with product and engineering teams
• Experience designing and implementing data models, data pipelines, and integration solutions
• Proven ability to mentor junior engineers and provide technical leadership

• Experience with dashboarding and application development using React and/or Streamlit
• Experience working with pre-clinical data, laboratory systems, and scientific stakeholders
• Experience with AI-assisted schema development and data parsing workflows
• Experience building reusable Python libraries and productized data-engineering solutions
• Exposure to ELN, LIMS, CRO, CDMO, manufacturing, and R&D laboratory data environments

• Tech Breakdown
• Python & SQL Data Engineering
• Scientific Data Modeling & Integration
• AI-Assisted Schema Development & Data Parsing
• Dashboard & Application Development (React, Streamlit, Jupyter)
• Architecture, Leadership & Mentoring

• Design and build scientific data pipelines, integrations, and reusable data products
• Collaborate with Product Managers and Solution Architects to define requirements and solutions
• Build schemas, parsers, and integration frameworks for scientific and laboratory data sources
• Lead technical design sessions and architectural decisions
• Mentor junior Scientific Data Engineers and improve team delivery practices
• Ensure quality through testing, code reviews, and engineering best practices
• Support customer implementations and validate business outcomes