Join TetraScience, 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 TetraScience'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. Required Skills & Experience 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 Desired Skills & Experience 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 What You Will Be Doing 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 Daily Responsibilities 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