Senior Scientific Data Engineer

TetraScience

. Act as a forward deployed engineer for a portfolio of biotech, pharmaceutical, and scientific customers.

Posted 10/14/2026full-timeRemote • United StatesSenior💰 $140,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building data products and integrations within the biotech and pharmaceutical sectors, leveraging strong technical skills in Python, SQL, and cloud engineering on AWS. Capable of leading cross-functional teams, managing project delivery, and mentoring junior engineers while ensuring compliance with regulated environments.

Highest-signal resume keywords

Python DevelopmentData IntegrationCloud Engineering on AWSCustomer-Facing ImplementationBiotech and Pharmaceutical Industry Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSQLJavaScriptTypeScriptNodeReactCI/CDFull Stack DevelopmentData Schema DesignTest Automation

Soft Skills

Excellent CommunicationAttention to DetailLeadershipCollaborationProblem-Solving

Tools & Technologies

Tetra OSELNLIMSMESAWS S3AWS LambdaAWS ECSAWS SQSAWS SNSAWS EC2

Industry Keywords

BiotechPharmaceuticalScientific WorkflowsGxPNon-Clinical Data

Tech Stack

Tools & technologies

AWSCloudEC2JavaScriptNode.jsPythonReactSQLTypeScript

About the role

Key responsibilities & impact

Act as a forward deployed engineer for a portfolio of biotech, pharmaceutical, and scientific customers.
Own the technical relationship, understand customers’ scientific workflows, and deliver solutions that move their programs forward.
Design and build bidirectional integrations between Tetra OS and customer systems such as ELN, LIMS, MES, and process historians.
Build serverless push and pull pipelines, stateful connectors, and full stack data applications in Python and TypeScript.
Design and build data schemas and parsers for scientific data from laboratory, manufacturing, CRO, CDMO, ELN, and LIMS sources.
Deploy and test solutions in customer cloud, on-premises, and hybrid environments.
Troubleshoot across the full stack when issues occur.
Collaborate with product managers, solution architects, business analysts, data architects, and ML engineers to understand requirements and build data products.
Create and enforce designs supported by comprehensive test automation.
Lead process and technology improvements for product quality, developer experience, and platform capabilities.
Rally the team to complete Agile sprint commitments and resolve inefficiencies.
Resolve blockers and unclear requirements with pragmatic urgency.
Mentor junior scientific data engineers and demonstrate leadership.

Requirements

What you’ll need

8+ 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, 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 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 core services such as S3, Lambda, ECS, SQS, SNS, EC2, and CloudWatch.
Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
Ability to quickly understand a highly technical product and communicate effectively with customers, product management, engineering leadership

Benefits

Comp & perks

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