Analytics Engineer - Data Science Industrialization

About the role

Pfizer's Industrialization team, within Enterprise Data Science and Advanced Analytics, leads the scaling of data and insights capabilities. As an Analytics Engineer you will build and maintain industrialized analytic data and code assets that power key business applications, joining a global team that develops data pipelines, optimizes feature creation and manages the performance of data and code assets.

Key responsibilities

• Implement at scale industrialized data science capabilities and analytic products
• Implement parametrized workflows and reusable widgets in the delivery of AI/ML analytic insight products
• Provide analytics engineering support to data science agile teams
• Implement CI/CD orchestration for data science pipelines
• Use data wrangling to build pipelines that ingest and integrate data from many sources and deliver high-quality data products
• Translate data needs into programmatic queries and convert Python-based data wrangling into PySpark/SQL pipelines
• Conduct data profiling and quality checks, and develop automated, self-monitoring pipelines with automated QA/QC

Required profile

• Bachelor's degree in analytics engineering, data science, computer engineering, computer science, information systems or a related discipline
• 2+ years of work experience as an analyst or analytics engineer
• Hands-on analytics engineering and data science skills
• Experience with structured and unstructured data, and understanding of data ingestion, warehousing and data models
• Knowledge of relational and dimensional data structures
• Strong English communication skills (written and verbal)

Required skills

• Python, R, SQL and industrialized ETL software
• Nice to have: visualization libraries such as D3, React and Angular
• Nice to have: CI/CD tools such as GitHub, GitHub Actions or Jenkins
• Nice to have: cloud analytics ecosystems (AWS, Snowflake) and containerization (AWS EKS, Kubernetes)
• Nice to have: data pipeline orchestration (Airflow) and CRISP data science lifecycle