Tech Lead/Manager, Scientific Data Engineering
About the role
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.
Responsibilities
- Lead a team of Scientific Data Engineers (SDE) and help build Tetra Data and productizable solutions, the foundation of the Data Engineering layer.
- Manage engineering tasks, lead internal design sessions, implement solutions, and drive projects to final production releases.
- Work directly with cross‑functional teams like Product Managers, Scientific Business Analysts, and Solution Architects to gather business and data design objectives, resulting in production‑based solutions.
- Supervise and collaborate on project executions, mentor junior team members, and manage team career growth and performance.
- Take ownership of building data models, prototypes, and solutions that drive customer success.
- Use LLMs to build comprehensive data schemas and parsers for pre‑clinical data (main sources: R&D lab instruments, manufacturing, CRO, CDMO, ELN, LIMS) with various formats: .xlsx, .pdf, .txt, .raw, .fid, many 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.
- Drive value for customers – verify the solution fulfills requirements and provides value.
- Act as quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions.
- Promote team‑wide process/technology improvements on product quality and developer experience.
- Rally the team to finish Agile Sprint commitments, surface inefficiencies, and resolve them.
- Be driven by results, with pragmatic urgency to resolve blockers, unclear requirements, and make things happen.
Requirements
- 10+ years of building solutions as a Data Engineer or similar fields.
- 10+ years working in Python and SQL with a focus on data.
- Experience managing engineering teams with five or more direct reports; experience leading projects, managing requirements, and handling timelines.
- Experience managing multiple customer‑focused implementation projects across cross‑functional teams, building sustainable processes, and managing delivery milestones.
- Experience with data plotting/dashboarding tools like React and/or Streamlit is strongly preferred.
- Experience working with pre‑clinical data and lab scientists is strongly preferred.
- Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
- Ability to quickly understand a highly technical product and effectively communicate with product management and engineering.
This position is not eligible for visa sponsorship.