Sr Associate, Data Science Platform Engineer

Key Skills

Java Programming, Python Programming, Database, SQL, DevOps, Azure, AWS, Big Data Technology, Apache Hadoop, Machine learning techniques, Data science techniques, JIRA, Kubernetes-K8s, Google Cloud Platform (GCP), SPARK Programming, Confluence, SharePoint

Job Description

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 Analytics & Data org within Digital Health, Medicines, and Artificial Intelligence, is responsible for the 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 Platform Engineers who are responsible managing components that form the enterprise analytics platform, Pfizer Insights. Pfizer Insights will be the digital engine that brings together investments we have made into a unified experience for colleagues that take us to the next level of value creation. It powers next generation insights by developing enterprise-grade data foundations, allowing data to flow horizontally, enabling a versatile analytics environment, and embedding insights into day-to-day work to create a digital, data-driven culture.

In this role, you will act as an engineer 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 engineering of the platform and hands on working knowledge creating data science applications 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

• Support the operations of multiple Dataiku DSS environments globally – and supporting self-service tenants
• Manage and resolve critical support issues with a high degree of technical complexity. 
• Document knowledge in the form of incident notes, technical articles, and contributions to knowledge bases or forums within specific areas of expertise. 
• Measure and monitor service and support performance and health (SLAs, KPIs, etc.)
• Partner with User Success team to maintain key informational content, drive platform adoption, and champion a strong user community
• Collaborate with engineering and support teams on platform lifecycle management
• Develop and maintain operational run-books and training curricula for support teams
• Directly engage and communicate with key business and technical stakeholders

 BASIC QUALIFICATIONS

• BS in computer science, data science, /or an engineering/quantitative
• At least 3 years of professional experience 
• Experience with engineering or technical role experience, ideally involving a complex and rapidly evolving software/product 
• Strong Linux system administration experience. 
• Comfort working with and reading code. 
• Experience working with at least one type of relational database and SQL. 
• Some experience with python. 
• Grit when faced with technical issues?- you don't rest until you understand what is happening and why things are not working. 
• Excellent problem solving and analytical skills with an aptitude for learning new technologies. 
• Strong communication skills and the ability to interface with both technical and non-technical individuals as needed. 
• Hands-on experience with DevOps and information tools – e.g., JIRA, Confluence, SharePoint, Yammer, etc. 

PREFERRED QUALIFICATIONS 

• Experience with big data technologies, such as Hadoop, Spark, or Kubernetes. 
• Experience with cloud platforms such as AWS, Azure, and GCP. 
• Some knowledge of data science / machine learning 
• Some knowledge of Java