Pfizer's Chief Digital Office (CDO) leads the transformation of Pfizer into a digital powerhouse that will generate patient superior experiences which results in better health outcomes.

The Analytics Experience team, which is part of the Artificial Intelligence, Data and Analytics organization is responsible for creating a seamless experience for analytics experts to harness the potential of big data, machine learning, and interactive analytics through a unified platform across the enterprise - from scientific/clinical to commercial across all Pfizer geographies.

Part of the Analytics Experience team are a group of Data Engineers who are responsible for creating cross business unit re-usable data products for the enterprise. These analytical ready data products act as a foundational asset for our end users of the Virtual Analytics Workspaces platform. These data products are leveraged as standard inputs to web applications, plugins, dashboards, and machine learning models. The data products produced by the team will be robust and provide the building blocks for analytics created on the platform. Data engineers are expected to help create, drive, and implement key best practices and features for re-usable cross domain data products across the Pfizer eco-system.

In this role, you will act as a data engineering expert for the Data Science platform that serves a diverse group of colleagues - ranging from novice business analysts to expert data scientists - across the enterprise. The role will require the ability to flex between technical data engineering expertise (creating ETL's from source data sets into useable analytical ready data products), and hands on working knowledge developing data product solution strategies as a user of the platform.

You may have a software development background, or an engineering background or you were raised in a modern data analytics culture from the start of your career. You will have the ability to work with technology vendors, support resources, delivery partners, Pfizer stakeholders, and apply emerging and traditional technologies for analytics improvements in support of enterprise analytics platform strategy.