Data Engineer; Hybrid

Company Description

About Abb Vie

Abb Vie's mission is to discover and deliver innovative medicines and solutions 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 including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  Follow @abbvie on Linked In, Facebook, Instagram, X and You Tube.

The Data Engineer will design and build scalable data-pipelines across initiatives such as agentic trail design, digital twins and other modeling & simulation use cases. Unleash the full potential of Abb Vie’s data assets by bringing technology and/or data and insights to the forefront of decision making via fit-for-purpose data and modeling solutions. Broaden the scope and impact of data by constantly exploring new opportunities to transform clinical development and R&D.

Collaborate with stakeholders to outline the problem, explore solutions, refine opportunities and deliver a product with a continuous innovation mindset. The data engineer will leverage a combination of modern cloud based and AI tools,agent frameworks, AI co-pilots and code generation tools for building the data-pipes. The hired associated will partner closely with internal stakeholders such as statisticians, stats programmers, data scientists, and other business teams to understand user needs, and rapidly iterate on building data solutions, and evolve successful use cases into reusable capabilities.

Additionally, based on need the data engineer with partner with IT for enabling necessary technology tools by defining requirements and follow through on the deployment.

• Collaborates with Statisticians &Data Scientists to enable streamlined data flow for the Data Science and Analytics capabilities across clinical development.
• Develop, construct, test and maintain architectures (such as databases and large-scale process systems) to support Modeling & Analytics projects with in Clinical Development
• Build data products and service processes which perform data transformation, metadata extraction, workload management and error processing management
• Implement standardized, automated operational and quality control processes to deliver accurate and timely data and reporting
• Adhere to best practices for coding, testing and designing reusable code/component
• Contribute to the discovery and understanding of new tools, and techniques and propose improvements to the data pipeline
• Develop data set processes for data modeling, mining and production
• Ensures adherence to federal regulations and applicable local regulations, Good Clinical Practices (GCPs), ICH Guidelines, Abb Vie Standard Operating Procedures (SOPs), and to functional quality standards. Stays abreast of new and/or evolving local regulations, guidelines and policies related to clinical development

Qualifications
:

• MS or PhD in statistics, mathematics, computer science or other quantitative disciplines with 2-3 years of experience
• 1+ year experience within building production-grade data solutions using modern AI frameworks such as Lang Graph, Lang Chain, Strands Agents, etc.
• Experience with one or more general purpose programming languages, including but not limited to:
  Java, Python, Scala, C, C++, C#, Swift/Objective C, or Java Script
• Experience with Big Data Management, Master Data Management tools & SQL

• 1+ years' experience in Amazon Web Services including admin modules preferred
• Experience in publishing analytics output in R Shiny and/or Plotly Dash is preferred
• End-to-end experience with data, including querying, aggregation, analysis, and visualization;
  Fluency in both structured and unstructured data (SQL, NOSQL) preferred
• Biotech / Pharma experience is a plus

• Good communication and presentation skills, being able to explain complex problems and the solutions applied, and comfortable in presenting technical solutions to a nontechnical audience
• Demonstrated history of successful execution in a fast-paced environment and in managing multiple priorities effectively

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state orlocal law:

• The compensation range described below is the range of possible base pay compensation that the…