Senior Associate, Data Engineer

At Pfizer we make medicines and vaccines that change patients' lives with a global reach of over 1.1 billion patients. Pfizer Digital is the organization charged with winning the digital race in the pharmaceutical industry. We apply our expertise in technology, innovation, and our business to support Pfizer in this mission.  

Our team, the Operations & Insights Team, is passionate about using software and data to improve manufacturing processes.  We partner with other Pfizer teams focused on: 

• Manufacturing throughput efficiency and increased manufacturing yield 

• Reduction of end-to-end cycle time and increase of percent release attainment  

• Increased quality control lab throughput and more timely closure of quality assurance investigations 

• Increased manufacturing yield of vaccines 

• More cost-effective network planning decisions and lowered inventory costs 

In the ​Senior Associate, Data Engineer​ role, you will help implement data capabilities within the team to enable advanced, innovative, and scalable database services and data platforms.  You will utilize modern Data Engineering principles and techniques to help the team better deliver value in the form of AI, analytics, business intelligence, and operational insights.  You will be on a team responsible for executing on technical strategies, designing architecture, and developing solutions to enable the Digital Manufacturing organization to deliver value to our partners across Pfizer. 

Most of all, you’ll use your passion for data to help us deliver real value to our global network of manufacturing facilities, changing patient lives for the better! 

ROLE RESPONSIBILITIES  

The ​Senior Associate, Data Engineer​’s responsibilities include, but are not limited to: 

• Modeling data sets and contextualizing business processes in schemas and graph models 

• Maintain Database Service Catalogues 

• Build, maintain and optimize data pipelines 

• Support cross-functional teams with data related tasks 

• Troubleshoot data-related issues, identify root causes, and implement solutions in a timely manner 

• Automate builds and deployments of database environments 

• Support development teams in database related troubleshooting and optimization 

• Document technical specifications, data flows, system architectures and installation instructions for the provided services 

• Collaborate with stakeholders to understand data requirements and translate them into technical solutions 

• Participate in relevant SAFe ceremonies and meetings 

BASIC QUALIFICATIONS  

• Education: Bachelor’s degree or Master’s degree in Computer Science, Data Engineering, Data Science, or related discipline 

• 3+ years of experience in Data Engineering, Data Science, Data Analytics or similar field 

• Broad Understanding of data engineering techniques and technologies, including at least 3 of the following: 

• PostgreSQL (or similar SQL database(s)) 

• MongoDB (or similar NoSQL database(s)) 

• ETL (Extract, Transform, and Load) processes 

• Airflow or other Data Pipeline technology 

• Kafka Distributed Event Streaming platform 

• Neo4J/Graph Databases 

• Experience tuning and optimizing database performance 

• Knowledge of modern data integration patterns 

• Strong verbal and written communication skills and ability to work in a collaborative team environment, spanning global time zones 

• Proactive approach and goal-oriented mindset 

• Self-driven approach to research and problem solving with proven analytical skills 

• Ability to manage tasks across multiple projects at the same time 

PREFERRED QUALIFICATIONS 

• Pharmaceutical Experience 

• Experience working with Agile delivery methodologies (e.g., Scrum) 

• Experience with Graph Databases 

• Experience with Snowflake/PostgreSQL 

• Experience with Kafka streaming 

• Proficiency in at least one development language, with a preference for Python 

• Familiarity with cloud platforms such as AWS  

• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes