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Associate Engineering Fellow -Process Knowledge & Data Architecture

Pay
$154,400–242,550/yearAnnual period assumed — pay source
U.S. Base Salary Range: $154,400.00 - $242,550.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. For information about our benefits, please click here.
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Work setting
Not stated
Employment
Full-time — employment source
Time Type Full time Job Exempt
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and govern connected data architecture linking chemistry, process, and analytical data

  • Build data pipelines that feed mechanistic models, digital twins, and AI/ML work

  • Define metadata models, ontologies, and FAIR data standards

  • Establish data governance covering quality, traceability, and cGMP compliance

  • Build dashboards and reporting to support project and leadership decisions

From the employer’s posting
Design, implement, and govern integrated data architectures linking chemistry, process parameters, scale, equipment attributes, and analytical results
Build and maintain scalable data pipelines that transform laboratory and manufacturing data into reusable assets for mechanistic modeling, development of digital twins, and AI/ML applications
Define metadata models, ontologies, and data standards
Establish and enforce data governance frameworks, ensuring data quality, traceability, auditability, and lifecycle controls aligned with regulatory expectations (e.g., cGMP, data integrity)
Develop data access, visualization, and reporting capabilities (e.g., dashboards)

What you’ll bring

All qualifications

Core experience

  • Strong expertise in data architecture, data modeling, and data integration, preferably within pharmaceutical R&D or manufacturing environments.
  • Experience with regulatory data integrity requirements (e.g., ALCOA+)
  • Communication Skills -Able to express oneself clearly and concisely within team; documents issues and/or concerns concisely with colleagues; adjusts communication style as appropriate for the audience; timely and effectively communicates with senior management; technical writing skills to support authorship and approval of internal technical documents
  • Experience working with scientific data systems (e.g., ELN, LIMS, MES) and integrating laboratory and manufacturing datasets.
  • Demonstrated ability to successfully contribute across multiple scientific endeavors
  • Proven experience designing scalable data platforms and pipelines, including cloud-based architectures (e.g., AWS, Azure) and modern data stacks.
Qualification wording
Strong expertise in data architecture, data modeling, and data integration, preferably within pharmaceutical R&D or manufacturing environments.
Experience with regulatory data integrity requirements (e.g., ALCOA+)
Communication Skills -Able to express oneself clearly and concisely within team; documents issues and/or concerns concisely with colleagues; adjusts communication style as appropriate for the audience; timely and effectively communicates with senior management; technical writing skills to support authorship and approval of internal technical documents
Experience working with scientific data systems (e.g., ELN, LIMS, MES) and integrating laboratory and manufacturing datasets.
Technical - Subject matter expertise in a specific scientific area or areas. Demonstrated ability to successfully contribute across multiple scientific endeavors
Proven experience designing scalable data platforms and pipelines, including cloud-based architectures (e.g., AWS, Azure) and modern data stacks.
Education & alternatives
Required: - PhD in Chemical Engineering, Chemistry, Data Science, or related field with 7+ years of relevant experience, or - MS with 13+ years, or BS with 15+ years of relevant experience.
Apply at Takeda Pharmaceutical

Posting record

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Status in our records
Live
First seen by us
Sep 9, 202656 days ago
Recorded sightings
73
Last seen by us
Nov 4, 2026
Employer says posted
Aug 26, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Higher than most similar jobs

$154K–$243K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 56

Up longer than most. Similar jobs usually come down between day 6 and day 54.

From 10,824 similar postings that came down. Coming down is not always a hire.

Takeda Pharmaceutical is hiring

60 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • 8% of open jobs were reposted
Hiring record

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Where the posting names them
- Experience working with scientific data systems (e.g., ELN, LIMS, MES) and integrating laboratory and manufacturing datasets. - Proven experience designing scalable data platforms and pipelines, including cloud-based architectures (e.g., AWS, Azure) and modern data stacks. - Strong understanding of data governance, metadata management, and FAIR data principles.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use.  I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

OBJECTIVE: 

Synthetic Molecule Process Development (SMPD) is responsible for the development of robust, sustainable and cost-effective processes for the manufacture of new synthetic molecule pharmaceuticals, along with methods for achieving and controlling high standards of purity and quality. 

The Associate Engineering Fellow, Process Knowledge & Data Architecture will lead the design and implementation of a scalable, integrated data and knowledge architecture to support process development across SMPD. This role sits at the intersection of process science, data engineering, and digital strategy, enabling model-informed development and AI-driven workflows by transforming fragmented experimental and manufacturing data into structured, reusable knowledge assets.

Working across matrix teams, the individual will define and implement SMPD’s data and knowledge strategy, enable data-driven decision-making, model development, and digital workflows, transforming fragmented datasets into a unified, high-value knowledge layer that accelerates development, improves process understanding, and supports lifecycle management.

                                    

ACCOUNTABILITIES: 

  • Own SMPD’s Knowledge Layer: Lead the design, governance, and lifecycle management of structured reaction, process, vessel, and material databases, establishing a unified and reusable process knowledge layer.
  • Architect Connected Data Systems: Design, implement, and govern integrated data architectures linking chemistry, process parameters, scale, equipment attributes, and analytical results across laboratory and manufacturing environments (e.g., ELN, LIMS, PAT, MES).
  • Enable Model-Informed Development: Build and maintain scalable data pipelines that transform laboratory and manufacturing data into reusable assets for mechanistic modeling, development of digital twins, and AI/ML applications.
  • Drive FAIR & Data Standards: Define metadata models, ontologies, and data standards; enable ELN/PAT/TDP ingestion pipelines; and implement FAIR data principles to ensure data is findable, accessible, interoperable, and reusable.
  • Ensure Governance & Compliance: Establish and enforce data governance frameworks, ensuring data quality, traceability, auditability, and lifecycle controls aligned with regulatory expectations (e.g., cGMP, data integrity).
  • Drive Data Integration & Interoperability: Integrate disparate data sources and systems, eliminating silos and enabling a “single source of truth” across process development workflows.
  • Partner Across Functions: Collaborate with Process Development, Modeling, Automation, and Engineering teams to ensure data is generated, captured, and structured to support advanced analytics, modeling, and decision-making.
  • Bridge Science and Digital: Translate process development needs into data architecture and platform requirements, working closely with IT, data engineering, and digital teams to implement scalable, secure, and compliant solutions.
  • Enable Data-Driven Decision Making: Develop data access, visualization, and reporting capabilities (e.g., dashboards) that support project teams and leadership in making informed decisions.
  • Lead Technology Implementation: Support the selection, deployment, and integration of digital platforms (e.g., cloud environments, data lakes, APIs), ensuring scalability and alignment with enterprise architecture.
  • Shape Strategy & Sustainability: Define SMPD’s connected data and model roadmap, identify and close architecture gaps, and partner with IT and Digital teams to ensure interoperability and long-term platform sustainability.
  • Own Digital Twin Architecture & Governance: Define model standards, validation frameworks, version control, and lifecycle management for predictive and hybrid models deployed across development and manufacturing.
  • Champion Data Culture & Capability Building: Promote best practices in data management, standards, and reuse; train and support scientists and engineers in adopting digital tools and workflows.
  • Lead External Benchmarking & Best Practices: Stay informed on industry trends, emerging technologies, and regulatory expectations to continuously evolve SMPD’s data and knowledge capabilities.
  • Operate in Matrix Teams: Influence and align cross-functional stakeholders to deliver integrated data solutions without direct authority. Operates as a technical leader within matrix teams, influencing stakeholders and driving alignment across functions without direct authority.
  • Proactively identify vendors and builds relationships to gain access to technologies as needed to deliver against goals. 
  • Manage key vendor relationships across multiple projects as appropriate, and proactively affects resolution of issues arising at vendors.    
  • Represent Takeda and is an active member on pre-competitive collaborations with academic and industrial partners.
  • Responsible for authoring relevant sections of regulatory documents, reports and peer reviewed manuscripts.

EDUCATION, EXPERIENCE AND SKILLS: 

Education and Experience:

Required:

  • PhD in Chemical Engineering, Chemistry, Data Science, or related field with 7+ years of relevant experience, or
  • MS with 13+ years, or BS with 15+ years of relevant experience.
  • Strong expertise in data architecture, data modeling, and data integration, preferably within pharmaceutical R&D or manufacturing environments.
  • Experience working with scientific data systems (e.g., ELN, LIMS, MES) and integrating laboratory and manufacturing datasets.
  • Proven experience designing scalable data platforms and pipelines, including cloud-based architectures (e.g., AWS, Azure) and modern data stacks. 
  • Strong understanding of data governance, metadata management, and FAIR data principles.
  • Experience enabling analytics, modeling, or AI/ML applications through structured data frameworks.
  • Understanding of pharmaceutical process development and/or manufacturing workflows, including CMC and cGMP considerations.
  • Demonstrated ability to work in cross-functional, matrix environments, influencing stakeholders across scientific and technical domains.
  • Strong communication skills, with the ability to translate complex technical concepts into actionable insights for diverse audiences.

Optional (Preferred Qualifications)

  • Experience with ontologies, knowledge graphs, or semantic data models
  • Experience supporting digital twins, advanced process control, or hybrid modeling
  • Track record of driving enterprise data initiatives or platform deployments
  • Experience with regulatory data integrity requirements (e.g., ALCOA+)

Knowledge and Skills:

  • Analytical and Problem Solving Skills - Able to troubleshoot critical issues or problems using appropriate information and, determine causes and possible solutions 
  • Teamwork -- Ability to work well on global cross-functional teams.
  • Communication Skills -Able to express oneself clearly and concisely within team; documents issues and/or concerns concisely with colleagues; adjusts communication style as appropriate for the audience; timely and effectively communicates with senior management; technical writing skills to support authorship and approval of internal technical documents
  • Organization – Exercises good time management and prioritization skills to balance multiple project and departmental objectives
  • Technical - Subject matter expertise in a specific scientific area or areas. Demonstrated ability to successfully contribute across multiple scientific endeavors 
  • Knowledge Sharing - Ability to capture knowledge within the organization; improves solutions, processes, and deliverables through use of information; improves information capital by contributing experience, theories, deliverables, and models for others to use
  • Resource Management -Project management skills; ability to manage one’s time within individual, departmental, and corporate goals and timelines; management of internal and external resources (vendors)
  • External Involvement – Demonstrated involvement in professional community evidenced by presentation of scientific posters or lectures at professional conferences or events. Interacts with external vendors for projects
  • Leadership Skills – Develops and uses knowledge and interpersonal skills to appropriately influence and guide others towards the accomplishment of department/function goals and objectives.

TRAVEL REQUIREMENTS:

May require approximately 10% travel.

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices. 

For Location:

Cambridge, MA

U.S. Base Salary Range:

$154,400.00 - $242,550.00


The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. 


For information about our benefits, please click here.


EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

Locations

Cambridge, MA

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

Job Exempt

Yes

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Source details

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Pay
U.S. Base Salary Range: $154,400.00 - $242,550.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. For information about our benefits, please click here.
Location & working pattern

Cambridge, MA

- Shape Strategy & Sustainability: Define SMPD’s connected data and model roadmap, identify and close architecture gaps, and partner with IT and Digital teams to ensure interoperability and long-term platform sustainability. - Own Digital Twin Architecture & Governance: Define model standards, validation frameworks, version control, and lifecycle management for predictive and hybrid models deployed across development and manufacturing. - Champion Data Culture & Capability Building: Promote best practices in data management, standards, and reuse; train and support scientists and engineers in adopting digital tools and workflows.
More source context
- Experience with ontologies, knowledge graphs, or semantic data models - Experience supporting digital twins, advanced process control, or hybrid modeling - Track record of driving enterprise data initiatives or platform deployments
Work authorization
EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law. Locations

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