Tech Lead Scientific Data Engineering

• 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
• You will be leading a team of Scientific Data Engineers (SDE) and helping build Tetra Data and productizable solutions, which is the foundation of the Data Engineering layer. We are looking for a data engineering leader who is experienced, hands-on, and can also provide mentorship to junior team members
• As a tech lead/manager, you should be comfortable managing engineering tasks, leading internal design sessions, implementing solutions, and driving projects to final production releases. You will 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
• 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
• Manage a team of SDEs. Supervise their career growth and performance
• Work with cross-functional teams 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 solutions that drive customer success
• Use LLM 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
• 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
• Promote 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

Benefits

• Unlimited PTO
• 100% Company Paid Health, Dental & Vision
• Company Paid Life Insurance
• 401k Savings
• Company Paid Disability Insurance
• Equity Program

Experience with data plotting dashboarding tools like React and/or Streamlit is strongly preferredQuickly understand a highly technical product and effectively communicate with product management and engineeringExperience working with pre-clinical data and lab scientists is strongly preferredExcellent communication skills, attention to detail, and the confidence to take control of project delivery10+ years working in Python and SQL with a focus on data10+ years of building solutions as a Data Engineer or similar fieldsExperience leading projects, managing requirements, and handling timelinesExperience managing multiple customer-focused implementation projects across cross-functional teams, building sustainable processes, and managing delivery milestonesExperience manaing engineering teams with five or more direct reports