Senior Scientific Data Engineer

Description About Tetra Science Tetra Science  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. Tetra Science’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and  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.

What You Will Do You will join Tetra Science'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 Type Script.

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.

Work with product managers, solution architects, business analysts, data architects, and ML engineers to understand business requirements, recommend outcomes, and build best-in-class data products based on consensus.

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.

Rally the team to finish Agile sprint commitments. Actively surface team inefficiencies and resolve them.

Drive results. Bring pragmatic urgency to resolving blockers and unclear requirements, and make things happen.

Provide mentorship to junior scientific data engineers and show leadership on every front.

Requirements8+ years building data products as a Data Engineer or in a similar field.
8+ years working in Python and SQL with a focus on data, integrations, and scientific applications.

Expertise in Python and working knowledge of JavaScript, Type Script, 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 the biotech and pharmaceutical industry and regulated environments such as GxP.Familiarity with…