TetraScience is a Scientific Data and AI company with a mission to radically improve and extend human life. TetraScience combines the world's only open, purpose-built, and collaborative scientific data and AI cloud with deep scientific expertise across the value chain to accelerate and improve scientific outcomes. TetraScience is catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which it brings to life in a growing suite of next generation lab data management products, scientific use cases, and AI-based outcomes
Our core values are designed to guide our behaviors, actions, and decisions such that we operate as one. We are looking to add high-performance team members that authentically and unconditionally embrace our values:
- Transparency and Context - We trust our people will make the right decisions and overcome any challenges when given data and context.
- Trust and Collaboration - We believe there can only be trust when there is transparency. We are committed to always communicating openly and honestly.
- Fearlessness and Resilience - We proactively run toward challenges of all types. We embrace uncertainty and we take calculated risks.
- Alignment with Customers - We are completely committed to ensuring our customers and partners achieve their missions and treat them with respect and humility.
- Commitment to Craft - We are passionate missionaries. We sweat the details, as the small things enable the big things.
- Equality of Opportunity - We seek out the best of the best regardless of gender, ethnicity, race, or age; We seek out those who embody our common values but bring unique and invaluable perspectives, talents, and advantages.
What You Will Do
You will be a Senior member of the Scientific Data Engineer team and helping build Tetra Data and productizable solutions, which is the foundation of the Data Engineering layer. We are looking for a player-coach data engineer who is experienced, hands-on, and can also provide mentorship to junior team members. As a Senior Scientific Data Engineer, you should be comfortable leading internal design sessions and architecting solutions. You will work directly with Product Managers and Solution Architects to gather business and data design objectives, resulting in production-based solutions. As a Senior Scientific Data Engineer, you will be a team-focused leader, have excellent data engineering skills, supervise and collaborate on project executions, and have a high commitment to customer success by delivering mission-critical implementations.
Our success is defined by collaboration. You will have tremendous support to achieve your objectives, from a variety of teams, both internal and external.
- Work with Product Managers and Solution Architects to understand business requirements, gather insight into potential positive outcomes, recommend potential outcomes, and build a solution based on consensus.
- Take ownership of building data models, prototypes, and integration solutions that drive customer success.
- Use AI agents to build comprehensive data schemas and parsers for pre-clinical data (main data sources: R&D lab instruments, manufacturing, CRO, CDMO, ELN, LIMS) with various data formats: .xlsx, .pdf, .txt, .raw, .fid, many other vendor binaries
- Extract reusable schema components and parsing functions, and productize them into Python libraries
- Build high-quality data pipelines with full unit test and integration test coverage to produce high-fidelity data
- Build data applications, reports, and dashboards using React, Streamlit, Jupyter notebook, etc.
- Work closely with product managers, project managers, business analysts, data architects, and ML engineers to deliver best-in-class data products
- Drive value for the customers - verify the solution fulfills their requirements and provides value
- Quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions.
- Lead team-wide process/technology improvements on product quality and developer experience
- Rally the team to finish Agile Sprint commitments. Actively surfacing team inefficiencies and striving to resolve them.
- Driven by results. Have the pragmatic urgency to resolve blockers, unclear requirements, and make things happen.
- Provide mentorship to junior SDEs and show leadership in every front
