Job Description

?ROLE SUMMARY ?

Do you want to make an impact on patient health around the world? Do you thrive in a fast-paced environment that brings together scientific, clinical and commercial domains through engineering, data science, and analytics? Then join Pfizer Digital's Artificial Intelligence, Data, and Analytics organization (AIDA) where you can leverage cutting-edge technology to inform critical business decisions and improve customer experiences for our patients and physicians. Our collection of engineering, data science, and analytics professionals are at the forefront of Pfizer's transformation into a digitally driven organization leveraging data science and advanced analytics to change patient's lives. The Industrialization team within Enterprise Data Science and Advanced Analytics leads the scaling of data and insights capabilities - critical drivers and enablers of Pfizer's digital transformation.

As a senior associate analytics engineer, you will be part of the Data Science Industrialization team charged with building and automating high quality data pipelines that power advanced analytics/AI/ML and key business applications. You will be a member of a global team helping to develop and innovate on commercial go-to-market strategies.

?ROLE RESPONSIBILITIES ?

• Leverage data wrangling techniques to deliver data pipelines that Ingest and integrate data from various information sources and deliver high quality data products that drive analytics and data science applications
• Translate data needs into intro programable queries and convert Python based data wrangling code into PySpark/SQL pipelines for scalable pushdown execution
• Conduct basic data profiling and quality checks
• Fine tune performance on datasets for visualization and other applications
• Develop automated and self-monitoring data pipelines including automated QA/QC processes
• Work with stakeholders to assist with data-related technical issues and support data infrastructure needs.

?QUALIFICATIONS ?

BASIC QUALIFICATIONS

• Bachelor's degree in analytics engineering related area (Data Science, Computer Engineering, Computer Science, Information Systems or related discipline)
• 2+ years of work experience as an analyst/analytics engineer for a diverse range of projects
• Strong hands-on skills in analytics engineering (e.g., Python, industrialized ETL software)
• Experience working in a cloud based analytics ecosystem (AWS, Snowflake, etc)
• Experience with working with various types of data (structured / unstructured)
• Understanding of data ingestion, data warehousing, and data model concepts
• Knowledge of relational and dimensional data structures, theories, and practices
• Proficient in SQL, Python
• 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 aptitude for learning new technologies and analytics techniques.

PREFERRED QUALIFICATIONS

• Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems or related discipline
• Experience with Dataiku is a plus
• Hands on experience working in Agile teams, processes, and practices
• Experience with hands-on skills in containerization (e.g. AWS EKS, Kubernetes)
• Experience with hands-on skills for data pipeline orchestration (e.g. Airflow)
• Understanding of data science development lifecycle (e.g CRISP)
• Pharma & Life Science commercial functional knowledge is a plus
• Pharma & Life Science commercial data literacy is a plus

Work Location Assignment: Flexible

#LI-PFE

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