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. 

ROLE RESPONSIBILITIES  

• With supervision, you will support the creation, development, and long term ownership of key analytical data products 

• With supervision, you will develop technical architecture and support diagrams as a part of the data product creation and maintenance process 

• Understand the data product lifecycle and management 

• Generate and maintain communications regarding key creations of net new data products, updates to existing data products, and archival or sunsetting of past data products 

• Document knowledge in the form of technical articles, and contributions to knowledge bases or forums within specific areas of expertise

• Develop and maintain operational run-books and training curricula for internal team and end users 

• Collaborate with cross functional teams of software engineers, data scientists, and analysists to maintain key technical and strategic information needed to develop a data product 

• Directly engage and communicate with key business and technical stakeholders  

 BASIC QUALIFICATIONS  

• BS in computer science, data science, /or an engineering/quantitative field

• 3+ years of professional experience 

• Experience with assembling large, complex, disparate data sources into re-usable data products that meet non-functional and functional business requirements 

• Identifying, designing and implementing process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes 

• Building required infrastructure for optimal extraction, transformation and loading of data from various data sources 

• Automating data pipelines, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition 

• Comfort working with and reading code (SQL, python, R, etc). 

• Grit when faced with technical issues - you don't rest until you understand what is happening and why things are not working

• Strong communication skills and the ability to interface with both technical and non-technical individuals as needed 

• Excellent problem solving and analytical skills with an aptitude for learning new technologies

• Hands-on experience with DevOps and information tools – e.g., JIRA, Confluence, SharePoint, Yammer, etc. 

PREFERRED QUALIFICATIONS 

• Experience with big data technologies, such as Snowflake, Spark, or Kubernetes

• Experience with platforms such as AWS, Azure, GCP, Dataiku 

• Some knowledge of data science / machine learning 

• Some experience working with at least one type of relational database and SQL 

• Some experience with Snowpark, Pyspark, Spark