Data Engineer, AI Enablement

Role: Data Engineer specializing in AI enablement within AbbVie's R&D data transformation initiative, focusing on building trusted, scalable, AI-ready data products for research analytics and knowledge graph capabilities. Responsibilities: design, develop, and operate curated data pipelines and assets from diverse sources; establish reliable data foundations supporting analytics, machine learning, and AI use cases; prepare and standardize data for AI and knowledge discovery, including metadata and vector database readiness; enforce data quality, governance, lineage, and documentation standards; collaborate with cross-functional teams to translate scientific and business requirements into dependable data solutions; monitor operational performance, troubleshoot issues, and contribute to process automation and improvements; ensure compliance with GxP, data security, and regulatory standards. Qualifications: Bachelor's (5+ years) or Master’s (4+ years) in IT, data management, or related field; proficiency in SQL, Python, ETL/ELT, workflow orchestration tools like Airflow; experience with data platforms, cloud environments, and analytics enablement; strong understanding of data curation, governance, and metadata practices; ability to operate independently and coordinate technical work across teams; excellent communication skills. Preferred: experience in healthcare or pharmaceutical research data environments; familiarity with graph databases, knowledge graphs, linked data, and cloud platforms such as AWS, Databricks, Snowflake; exposure to ML, retrieval-augmented generation, embeddings, and AI-ready data delivery; Agile methodologies. Location: Not specified; likely hybrid or remote with cross-functional stakeholder engagement.