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Pfizer

Manager, AI and Analytics Data Engineer

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Hybrid
2 Locations
Hybrid
2 Locations

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As a Senior Associate in Data Solutions Engineering, you'll develop data warehouse solutions, build data pipelines, and provide analytics insights to enhance Pfizer's operations.
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Do you want to make a global impact on patient health? Join Pfizer Digital's Artificial Intelligence, Data, and Advanced Analytics organization (AIDA) to leverage cutting-edge technology for critical business decisions and enhance customer experiences for colleagues, patients, and physicians. Our team is at the forefront of Pfizer's transformation into a digitally driven organization, using data science and AI to change patients' lives. The Data Science Industrialization team leads engineering efforts to advance AI and data science applications from POCs and prototypes to full production.
As a Manager, AI and Analytics Data Engineer, you will be part of a global team responsible for designing, developing, and implementing robust data layers that support data scientists and key advanced analytics/AI/ML business solutions. You will develop data solutions to support our data science community and drive data-centric decision-making.
Join our diverse team in making an impact on patient health through the application of cutting-edge technology and collaboration.
ROLE RESPONSIBILITIES
  • Develop data solutions to support data scientists and analytics/AI solutions, ensuring data quality, reliability, and efficiency
  • Conduct exploratory data analysis and quality checks
  • Deliver scalable data pipelines that ingest and integrate data from various information sources
  • Contribute to best practices, standards, and documentation to ensure consistency and scalability
  • Conduct data engineering research to advance design and development capabilities
  • Guide junior developers on concepts such as data modeling, database architecture, data pipeline management, data ops and automation, tools, and best practices
  • Demonstrate a proactive approach to identifying and resolving potential system issues
  • Create and maintain robust technical documentation for data solutions to enable knowledge retention and sharing
  • Collaborate with data scientists, engineers, and colleagues from across Pfizer to integrate AI and data science models into production solutions
  • Partner with the AIDA Data and Platforms teams to enforce best practices for data engineering and data solutions

BASIC QUALIFICATIONS
  • Bachelor's degree in computer science, information technology, software engineering, or a related field (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering, or a related discipline).
  • 5+ years of hands-on experience in working with SQL, Python, object-oriented scripting languages (e.g. Java, C++, etc..) in building data pipelines and processes. Proficiency in SQL programming, including the ability to create and debug stored procedures, functions, and views.
  • Knowledge of modern data engineering frameworks and tools such as Snowflake, Redshift, Spark, Airflow, Hadoop, Kafka, and related technologies
  • Experience working in a cloud-based analytics ecosystem (AWS, Snowflake, etc.)
  • Understanding of Software Development Life Cycle (SDLC) and data science development lifecycle (CRISP)
  • Highly self-motivated to deliver both independently and with strong team collaboration
  • Ability to creatively take on new challenges and work outside comfort zone.
  • Strong English communication skills (written & verbal)

PREFERRED QUALIFICATIONS
  • Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems, or a related discipline (preferred, but not required)
  • Experience with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker or other data science platforms
  • Familiarity with machine learning and AI technologies and their integration with data engineering pipelines
  • Familiarity with containerization technologies like Docker and orchestration platforms like Kubernetes.
  • Experience working effectively in a distributed remote team environment
  • Hands on experience working in Agile teams, processes, and practices
  • Proficiency in using version control systems like Git.
  • Pharma & Life Science commercial functional knowledge
  • Pharma & Life Science commercial data literacy

Ability to work non-traditional work hours interacting with global teams spanning across the different regions (e.g.: North America, Europe, Asia)
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
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