Associate Engineering Fellow -Process Knowledge & Data Architecture
Takeda
August 14, 2026
Remote friendly (Cambridge, MA)
United States
$154,400 - $242,550 USD yearly
IT
OBJECTIVE
Synthetic Molecule Process Development (SMPD) develops robust, sustainable, cost-effective processes for new synthetic molecule pharmaceuticals, ensuring high purity and quality.
Associate Engineering Fellow, Process Knowledge & Data Architecture
Lead the design and implementation of scalable, integrated data and knowledge architecture to support process development across SMPD, transforming fragmented experimental/manufacturing data into structured, reusable knowledge assets.
ACCOUNTABILITIES
- Own SMPD’s Knowledge Layer: design, governance, and lifecycle management of structured reaction, process, vessel, and material databases.
- Architect connected data systems across ELN, LIMS, PAT, MES.
- Enable model-informed development via scalable data pipelines for mechanistic modeling, digital twins, and AI/ML.
- Drive FAIR/data standards (metadata models, ontologies, ingestion pipelines).
- Ensure data governance and compliance (quality, traceability, auditability; cGMP/data integrity).
- Integrate disparate sources for a “single source of truth.”
- Partner across functions; translate science needs into data/platform requirements.
- Provide dashboards/reporting; implement digital platforms (cloud, data lakes, APIs).
- Define connected data/model roadmap and digital twin standards/validation/version control.
- Build data culture; benchmark technologies; influence matrix teams.
- Author regulatory documents/reports/manuscripts.
EDUCATION/EXPERIENCE (Required)
- PhD with 7+ years, or MS with 13+ years, or BS with 15+ years (Chemical Engineering/Chemistry/Data Science or related).
- Expertise in data architecture, modeling, integration (pharma R&D/manufacturing preferred).
- Experience with ELN/LIMS/MES; scalable cloud/data stacks (AWS/Azure); governance/metadata/FAIR.
- Experience enabling analytics/modeling/AI-ML; understanding pharma process development/CMC/cGMP.
PREFERRED
- Ontologies/knowledge graphs/semantic models; digital twins/advanced process control/hybrid modeling; enterprise data initiatives/platform deployments; ALCOA+.
SKILLS
Analytical/problem solving; teamwork; communication; organization; knowledge sharing; resource/project management; external involvement; leadership.
TRAVEL
~10%.
APPLICATION INSTRUCTIONS
Use the “Apply” button to submit your employment application.
Synthetic Molecule Process Development (SMPD) develops robust, sustainable, cost-effective processes for new synthetic molecule pharmaceuticals, ensuring high purity and quality.
Associate Engineering Fellow, Process Knowledge & Data Architecture
Lead the design and implementation of scalable, integrated data and knowledge architecture to support process development across SMPD, transforming fragmented experimental/manufacturing data into structured, reusable knowledge assets.
ACCOUNTABILITIES
- Own SMPD’s Knowledge Layer: design, governance, and lifecycle management of structured reaction, process, vessel, and material databases.
- Architect connected data systems across ELN, LIMS, PAT, MES.
- Enable model-informed development via scalable data pipelines for mechanistic modeling, digital twins, and AI/ML.
- Drive FAIR/data standards (metadata models, ontologies, ingestion pipelines).
- Ensure data governance and compliance (quality, traceability, auditability; cGMP/data integrity).
- Integrate disparate sources for a “single source of truth.”
- Partner across functions; translate science needs into data/platform requirements.
- Provide dashboards/reporting; implement digital platforms (cloud, data lakes, APIs).
- Define connected data/model roadmap and digital twin standards/validation/version control.
- Build data culture; benchmark technologies; influence matrix teams.
- Author regulatory documents/reports/manuscripts.
EDUCATION/EXPERIENCE (Required)
- PhD with 7+ years, or MS with 13+ years, or BS with 15+ years (Chemical Engineering/Chemistry/Data Science or related).
- Expertise in data architecture, modeling, integration (pharma R&D/manufacturing preferred).
- Experience with ELN/LIMS/MES; scalable cloud/data stacks (AWS/Azure); governance/metadata/FAIR.
- Experience enabling analytics/modeling/AI-ML; understanding pharma process development/CMC/cGMP.
PREFERRED
- Ontologies/knowledge graphs/semantic models; digital twins/advanced process control/hybrid modeling; enterprise data initiatives/platform deployments; ALCOA+.
SKILLS
Analytical/problem solving; teamwork; communication; organization; knowledge sharing; resource/project management; external involvement; leadership.
TRAVEL
~10%.
APPLICATION INSTRUCTIONS
Use the “Apply” button to submit your employment application.