Manager, AI and Analytics Data Engineer

Job Posted 2 Days Ago Posted 2 Days Ago
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2 Locations
Hybrid
Senior level
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
We’re in relentless pursuit of breakthroughs that change patients’ lives.
The Role
As a Manager, AI and Analytics Data Engineer, you will design, develop, and implement data solutions to support data scientists and AI applications. Responsibilities include creating scalable data pipelines, conducting data analysis, and collaborating with teams to integrate AI models into production while guiding junior developers.
Summary Generated by Built In

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.
Information & Business Tech
#LI-PFE

Top Skills

Airflow
AWS
C++
Docker
Hadoop
Java
Kafka
Kubernetes
Python
Redshift
Snowflake
Spark
SQL

What the Team is Saying

Person1
Daniel
Diagnostics Launch Lead
“Given the many available opportunities, colleagues with an entrepreneurial spirit thrive at Pfizer as they build relationships that lead to their engagement on breakthrough projects with high visibility“
Daniel
Anna
Esteban
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The Company
HQ: New York, NY
121,990 Employees
Hybrid Workplace
Year Founded: 1848

What We Do

Our purpose ensures that patients remain at the center of all we do. We live our purpose by sourcing the best science in the world; partnering with others in the healthcare system to improve access to our medicines; using digital technologies to enhance our drug discovery and development, as well as patient outcomes; and leading the conversation to advocate for pro-innovation/pro-patient policies.

Why Work With Us

We are the inventors, the problem solvers, the big thinkers — those who surmount any hurdle to deliver breakthrough medicines to the people who are counting on them the most.

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