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AbbVie’s mission is to discover and deliver innovative medicines that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people’s lives across several key therapeutic areas: immunology, oncology, neuroscience, eye care, virology, women’s health and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.

Development Sciences Data Architect/ Data Architecture Lead

Lake County, Illinois Req ID 2203867 Category Information Technology Division AbbVie

The Data Architecture Lead is an expert in treatment of “context” of scientific data. On top of proper management of data and meta data from both experiments and simulations, capturing data context is essential for efficient downstream data analysis (e.g. compilation of comparable sets) and reuse of data beyond their original purpose. Context can be stored in machine processible manner using a variety of approaches, ranging from controlled vocabulary, taxonomy and thesaurus to ontology. The Data Architecture Lead will actively participate in implementation of use cases to represent data model and data governance aspects. He/she will partner with Abbvie library and IR data engineering teams to determine the sweet spot for capturing context on illustrative examples. Supported by a team of embedded data stewards he/she will develop tangible data governance best practices and establish these within Dev Sci. Alignment with neighboring units outside Dev Sci is key to ensure synergistic data exchange with these communities. Pre-competitive engagements with initiatives, vendors, and peers outside Abbvie are key for continuous improvement of our capabilities.



  • Responsible for development & implementation of Dev Sci data standards and data governance best practices in collaboration with Dev Sci Use Case teams and scientists, Abbvie library and IR data engineering teams to ensure that Dev Sci scientific data is FAIR (findable, accessible, interoperable & reusable).
  • Establishes clear decision criteria for the optimal depth to capture “context” in machine processible manner (controlled vocabulary, taxonomy, thesaurus, ontology) on reference use cases.
  • Communicates data governance requirements to the Dev Sci community and drives alignment across scientific functions to ensure practices are well understood and followed.
  • Initiates and functionally leads a future Data Steward community (embedded in Dev Sci functions) and partners with Information Research to create, review & approve new data system catalog terms in the CENTree ontology management system and other relevant systems. Owns Dev Sci data contracts.
  • Interfaces with other data governance organizations and initiatives within Abbvie to coordinate “vocabulary” between research, operations, etc. Actively participates in communities outside Abbvie and reviews relevant literature to learn best practices from vendors and industry peers

Position can be hired as a Data Architect or a Data Architecture Lead based on the level of education and experience of the candidate. 



  • Bachelor’s Degree or equivalent education and typically 12 years of experience, Master’s Degree or equivalent education and typically 10 years of experience, PhD and typically 4 years of experience.
  • Relevant and credible/proven experience in the field of data context management
  • The ideal candidate brings a blend of strong scientific experience in the biotech/pharma industry and proficient IT skills.
  • Proven track record of evolving data architecture & solving data access challenges
  • Proven ability working in matrixed environment with diverse groups including subject matter experts, scientists & IT
  • Recognized and sought out as an expert in his/her discipline within the company and possibly externally.


Key Stakeholders:  Dev Sci scientists & leaders, Digital Transformation Use Case teams, Information Research partners


Significant Work Activities: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)Keyboard use (greater or equal to 50% of the workday)
Travel: No
Job Type: Experienced
Schedule: Full-time

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