Senior Scientific Data Engineer

TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.

In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.

You will join TetraScience's forward deployed teams as a senior, hands-on engineer. In this role, you will work directly with biotech, pharmaceutical, and scientific companies, bringing advanced data and AI technologies into the labs that research, develop, and manufacture medicines. You will work alongside customer scientific, engineering, and IT teams to design, build, and ship integrations and data products on Tetra OS that serve scientific teams across the globe. You will also mentor other scientific data engineers, lead internal design sessions, and partner with Product Managers and Solution Architects to turn customer, product, and engineering objectives into commercialized solutions.

• Act as a forward deployed engineer for a portfolio of biotech, pharmaceutical, and scientific customers. Own the technical relationship, understand their scientific workflows, and deliver solutions that move their programs forward.
• Drive AI agents to design and build bidirectional integrations between Tetra OS and customer systems such as ELN, LIMS, MES, and process historians, including serverless push and pull pipelines, stateful connectors, and full stack data applications in Python and TypeScript.
• Drive AI agents to design and build comprehensive data schemas and parsers for scientific data from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS sources, across formats such as .xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries.
• Deploy and test solutions in customer environments, including cloud, on-premises, and hybrid networks, and troubleshoot across the full stack when something breaks.
• Create and enforce designs with quality backed by comprehensive test automation to prove expected behaviors.
• Lead process and technology improvements supporting product quality, developer experience, and platform capabilities.
• Provide mentorship to junior scientific data engineers and show leadership on every front.

We hire Sciborg team members with potential, passion, and values alignment, not just a checklist of requirements. If you have related skills and a desire to learn, we want to hear from you.

• Demonstrated history building and delivering data products, integrations, and scientific applications as a Data Engineer or in a similar field.
• Expertise in Python and working knowledge of JavaScript, TypeScript, Node, React, SQL.
• Familiarity with networking, CI/CD, and full stack development.
• Familiarity with cloud engineering on AWS, including core services such as S3, Lambda, ECS, SQS, SNS, EC2, and CloudWatch.
• Familiarity with the biotech and pharmaceutical industry and regulated environments such as GxP.
• Experience working with non-clinical data and lab scientists.
• Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
• History leading customer-facing implementation projects across cross-functional teams, managing requirements, timelines, and delivery outcomes.

• Competitive Salary and equity in a fast-growing company.
• Generous paid time off (PTO).
• We are not currently providing visa sponsorship for this position

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