SciPro
Overview
SciPro has partnered with a rapidly growing, cloud-native healthtech company transforming how life sciences organizations structure and activate their data. With deep integration across the world’s leading cloud and AI platforms, this company is redefining how R&D data is collected, modeled, and leveraged to accelerate discovery.
Role We are seeking a
Senior Data Architect
to bridge the gap between complex scientific workflows and scalable digital solutions. In this role, you will collaborate with scientific stakeholders and cross-functional teams to design robust data architectures, enable AI/ML readiness, and deliver solutions that empower the biopharma and health industries to accelerate innovation.
This role is
based in Boston
(hybrid: primarily remote, but must be available for onsite client engagements as needed).
Key Responsibilities
Translate scientific and lab-based workflows into scalable, data-driven solutions
Architect and implement structured data models (SQL, NoSQL, JSON schemas, ontologies) tailored for scientific data
Develop Python-based pipelines for parsing, modeling, and integrating scientific datasets
Integrate lab systems (ELNs, LIMS, and other software) via APIs to support seamless workflows
Collaborate with customer stakeholders to gather requirements and deliver fit-for-purpose solutions
Present technical solutions and progress updates to both scientific and non-technical audiences
Identify reusable components to inform platform productization and future builds
Serve as a trusted technical and scientific partner to clients, driving long-term adoption and success
Core Qualifications
PhD with 7+ years or Master’s with 10+ years of experience in
Python (scale 8–9/10 coding ability)
for data architecture, engineering, or scientific applications
Experience integrating lab systems (ELNs, LIMS, APIs)
Familiarity with cloud platforms ( AWS required , Azure/GCP a plus)
Background in
life sciences
(biotech, pharma, health & wellness, or adjacent) — experience in a scientific setting is required
Experience in drug discovery, preclinical development, or CMC
Strong problem-solving and communication skills; ability to engage with scientists and stakeholders at various technical levels
Customer-facing experience and comfort leading discussions with external partners
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Science, Other, and Information Technology
Industries
Biotechnology
Data Infrastructure and Analytics
#J-18808-Ljbffr
Role We are seeking a
Senior Data Architect
to bridge the gap between complex scientific workflows and scalable digital solutions. In this role, you will collaborate with scientific stakeholders and cross-functional teams to design robust data architectures, enable AI/ML readiness, and deliver solutions that empower the biopharma and health industries to accelerate innovation.
This role is
based in Boston
(hybrid: primarily remote, but must be available for onsite client engagements as needed).
Key Responsibilities
Translate scientific and lab-based workflows into scalable, data-driven solutions
Architect and implement structured data models (SQL, NoSQL, JSON schemas, ontologies) tailored for scientific data
Develop Python-based pipelines for parsing, modeling, and integrating scientific datasets
Integrate lab systems (ELNs, LIMS, and other software) via APIs to support seamless workflows
Collaborate with customer stakeholders to gather requirements and deliver fit-for-purpose solutions
Present technical solutions and progress updates to both scientific and non-technical audiences
Identify reusable components to inform platform productization and future builds
Serve as a trusted technical and scientific partner to clients, driving long-term adoption and success
Core Qualifications
PhD with 7+ years or Master’s with 10+ years of experience in
Python (scale 8–9/10 coding ability)
for data architecture, engineering, or scientific applications
Experience integrating lab systems (ELNs, LIMS, APIs)
Familiarity with cloud platforms ( AWS required , Azure/GCP a plus)
Background in
life sciences
(biotech, pharma, health & wellness, or adjacent) — experience in a scientific setting is required
Experience in drug discovery, preclinical development, or CMC
Strong problem-solving and communication skills; ability to engage with scientists and stakeholders at various technical levels
Customer-facing experience and comfort leading discussions with external partners
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Science, Other, and Information Technology
Industries
Biotechnology
Data Infrastructure and Analytics
#J-18808-Ljbffr