Development Sciences Data Architect/ Data Architecture Lead

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Responsibilities:

• 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.

Qualifications:

Qualifications:

• 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.