• Responsible for data modeling and engineering within the advanced data platforms teams to achieve digital outcomes. Create test plans, test scripts, and perform data validation.
• Conceive, design, and implement Cloud Data Lake, Data Warehouse, Data Marts, and Data APIs.
• Develop complex data products that are beneficial for PGS and Allow for reusability across enterprise.
• Ability to collaborate with contractors to deliver technical enhancements.
• Develop automated systems for building, testing, monitoring, and deploying ETL data pipelines within a continuous integration environment.
• Develop internal APIs and data solutions to enhance application functionality and facilitate connectivity.
• Collaborate with backend engineering teams to analyze data, enhancing its quality and consistency.
• Conduct root cause analysis and address production data issues.
• Design, develop, and implement AI models and algorithms to solve sophisticated data analytics and supply chain initiatives.
• Stay abreast of the latest advancements in AI and machine learning technologies and apply them to Pfizer's projects.
• Provide technical expertise and guidance to team members and stakeholders on AI-related initiatives.
• Document and present findings, methodologies, and project outcomes to various stakeholders.
• Integrate and collaborate with different technical teams across Digital to drive overall implementation and delivery.
• Ability to work with large and complex datasets, including data cleaning, preprocessing, and feature selection

• A bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, or a related discipline.
• 3+ years of experience as a Data Engineer, Data Architect, or in Data Warehousing, Data Modeling, and Data Transformations.
• Over 1 years of experience in AI, machine learning, and large language models (LLMs) development and deployment.
• Proven track record of successfully implementing AI solutions in a healthcare or pharmaceutical setting is preferred.
• Strong understanding of data structures, algorithms, and software design principles
• Programming Languages: Experience in Python, SQL, and familiarity with Java or Scala.
• Big Data Technologies: Familiarity with Hadoop, Spark, and Kafka for big data processing.

PREFERRED QUALIFICATIONS