Data Engineer (Hybrid)

Role: Data Engineer responsible for designing and building scalable data pipelines to support clinical development and R&D initiatives at AbbVie. Primary objectives include leveraging modern cloud-based and AI tools to optimize data assets, enable modeling, simulation, and decision-making, and collaborate closely with statisticians, data scientists, and IT teams. Responsibilities encompass developing data architectures, automating data transformation processes, ensuring quality and compliance, and exploring new tools to improve data workflows. Qualifications: MS or PhD in a quantitative discipline with 2-3 years of experience, including 1+ year in building production-grade data solutions using AI frameworks like LangGraph, LangChain, or Strands Agents. Proficiency in programming languages such as Python or Java, experience with Big Data management, SQL, and cloud platforms like AWS are required. Preferred: experience with data visualization tools (R Shiny, Plotly Dash), unstructured data (NoSQL), and biotech/pharma experience. Skills: strong communication, ability to explain complex technical issues to non-technical stakeholders, and demonstrated success in fast-paced environments. High-Value: focus on data pipelines for clinical development, supporting modeling/simulation use cases, with a preference for experience in biotech or pharma settings, and familiarity with regulatory standards and GxP practices. Work setup: not specified.