Senior Scientific Data Engineer

TetraScience is seeking a Senior Scientific Data Engineer to join its forward-deployed teams. In this onsite role in New York, NY, you will design, build, and ship integrations and data products on Tetra OS for biotech, pharmaceutical, and scientific customers.

Responsibilities

• Serve as a forward deployed engineer for a portfolio of biotech, pharmaceutical, and scientific customers by owning the technical relationship, understanding scientific workflows, and delivering solutions that advance customer programs.
• Lead AI-driven initiatives to design and build bidirectional integrations between Tetra OS and customer systems, including ELN, LIMS, MES, and process historians, using serverless push and pull pipelines, stateful connectors, and full stack data applications in Python and TypeScript.
• Lead AI-driven initiatives to design and build comprehensive data schemas and parsers for scientific data originating from R&D lab instruments, manufacturing, CRO, CDMO, ELN, and LIMS, supporting formats including .xlsx, .pdf, .txt, .raw, .fid, and additional vendor binary formats.
• Deploy and test solutions in customer environments across cloud, on-premises, and hybrid networks, and troubleshoot across the full stack when issues arise.
• Collaborate with product managers, solution architects, business analysts, data architects, and ML engineers to interpret business requirements, recommend outcomes, and build data products aligned with team consensus.
• Create and uphold designs with quality supported by comprehensive test automation to validate expected behaviors.
• Drive process and technology improvements that strengthen product quality, developer experience, and platform capabilities.
• Support Agile sprint commitments by rallying the team to complete deliverables, surfacing inefficiencies, and working to resolve them.
• Maintain pragmatic urgency to address blockers and unclear requirements to drive measurable progress.
• Provide mentorship to junior scientific data engineers and demonstrate leadership across priorities.

Requirements

• 8+ years building data products as a Data Engineer or in a similar role.
• 8+ years working in Python and SQL with a focus on data, integrations, and scientific applications.
• Expertise in Python and working knowledge of JavaScript, TypeScript, Node, and React.
• Experience leading customer-facing implementation projects across cross-functional teams, including managing requirements, timelines, and delivery milestones.
• Experience working with non-clinical data and lab scientists.
• Familiarity with the biotech and pharmaceutical industry and regulated environments such as GxP.
• Familiarity with networking, CI/CD, and full stack development.
• Familiarity with cloud engineering on AWS, including S3, Lambda, ECS, SQS, SNS, EC2, and CloudWatch.
• Excellent communication skills, attention to detail, and confidence to take control of project delivery.
• Ability to quickly understand a highly technical product and communicate effectively with customers, product management, and engineering leadership.

Technologies

• Python, SQL
• JavaScript, TypeScript, Node, React
• AWS: S3, Lambda, ECS, SQS, SNS, EC2, CloudWatch
• CI/CD
• ELN, LIMS, MES, GxP
• Agile
• Serverless push and pull pipelines, stateful connectors

Compensation and Benefits

• Salary range: USD 140,000 - 200,000 per year
• Competitive compensation
• Stock options in a VC-backed Series C company
• 100% employer-paid benefits for all eligible employees and immediate family members
• 401(k)
• Unlimited paid time off (PTO)
• Flexible working arrangements
• Company-paid Life Insurance, LTD/STD