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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 10105282
- Position Id: 893109
- Posted 7 hours ago
