About the job
TetraScience is a pioneering company dedicated to transforming scientific data management through advanced AI technologies. Our mission is to significantly enhance and extend human life by leveraging the power of data. We offer the world's first open, purpose-built, and collaborative scientific data cloud, combined with unparalleled scientific expertise to drive better scientific outcomes. As a leader in the Scientific AI revolution, we are committed to creating AI-native scientific datasets and innovative lab data management products that address real-world scientific challenges.
We are seeking high-performing team members who resonate with our core values, which guide our actions and decisions:
- Transparency and Context: We empower our team to make informed, data-driven decisions.
- Trust and Collaboration: We believe trust is built through transparency and open communication.
- Fearlessness and Resilience: We embrace challenges, uncertainty, and calculated risks.
- Alignment with Customers: Our commitment is to our customers' success, treating them with respect and humility.
- Commitment to Craft: We are detail-oriented and believe that small things lead to significant outcomes.
- Equality of Opportunity: We welcome diverse perspectives and talents, ensuring equal opportunity for all.
Key Responsibilities:
As a Senior Scientific Data Engineer, you will play a vital role in developing Tetra Data and productizable solutions, which are crucial to our Data Engineering layer. We seek a hands-on, experienced engineer who can also mentor junior members of the team. You will lead design sessions and architect solutions while collaborating closely with Product Managers and Solution Architects to define business and data design objectives, resulting in effective, production-ready solutions. Your role as a team-oriented leader will involve supervising project execution and ensuring customer success through mission-critical implementations.
Your success will be supported by collaboration across various internal and external teams.

