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TetraScience is building Tetra OS, an operating system for scientific intelligence that helps life sciences companies transform fragmented scientific data into AI-native assets and workflows to accelerate discovery, development, and manufacturing. The company partners with industry leaders including NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
As a Senior Scientific Data Engineer on the forward-deployed team, you will be a hands-on engineer working directly with biotech, pharmaceutical, and scientific companies to bring advanced data and AI technologies into research, development, and manufacturing labs. You will own technical customer relationships, understand their scientific workflows, and deliver solutions that move their programs forward.
Key responsibilities include:
- Act as a forward-deployed engineer for a portfolio of biotech and pharmaceutical customers, owning the technical relationship and understanding their scientific workflows
- Design and build bidirectional integrations between Tetra OS and customer systems (ELN, LIMS, MES, process historians) using serverless pipelines, stateful connectors, and full-stack applications in Python and TypeScript
- Design and build comprehensive data schemas and parsers for scientific data from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS sources across multiple formats (.xlsx, .pdf, .txt, .raw, .fid, and vendor binaries)
- Deploy and test solutions in customer environments (cloud, on-premises, hybrid networks) and troubleshoot across the full stack
- Collaborate with product managers, solution architects, business analysts, data architects, and ML engineers to understand requirements and build data products
- Create designs backed by comprehensive test automation
- Lead process and technology improvements supporting product quality, developer experience, and platform capabilities
- Rally the team to complete Agile sprint commitments and surface team inefficiencies
- Provide mentorship to junior scientific data engineers and demonstrate leadership
Requirements:
- Proficiency in building data products as a Data Engineer or similar role
- Proficiency in Python and SQL with focus on data, integrations, and scientific applications
- Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React
- History leading customer-facing implementation projects across cross-functional teams, managing requirements, timelines, and delivery milestones
- Experience working with non-clinical data and lab scientists
- Familiarity with biotech and pharmaceutical industry and regulated environments (GxP)
- Familiarity with networking, CI/CD, and full-stack development
- Familiarity with AWS cloud engineering (S3, Lambda, ECS, SQS, SNS, EC2, CloudWatch)
- Excellent communication skills, attention to detail, and confidence in project delivery
- Ability to quickly understand highly technical products and communicate effectively with customers and leadership
