Pfizer
Pharma
Manager,DataEngineering
Neural analysis suggests this role is
optimal for Mid candidates.
“Manager, Data Engineering at Pfizer. Skills: Data Engineering, AI, Analytics, Data Modeling, Pipelines, Feature Stores, Machine Learning Models, Retrieval-Augmented Generation (RAG), Agentic Systems. Leads the development of core data components for our advanced analytics layer and agentic data layers.. Designs and builds end-to-end data pipelines and products specifically to power advanced AI and Retrieval-Augmented Generation (RAG) applications.”
What You'll Achieve.
Delivering new, innovative capabilities.; Enabling the business to remain competitive and innovative in a data-driven world.; Delivers the high-quality, performant data that forms the basis of meaningful recommendations and drives concrete strategic decisions for brand and commercial strategy.
Industry & Context.
Transforming data into actionable intelligence.; Solving the business's most challenging problems and create value.
What They're Looking For.
Must Have
Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Data Science, Engineering, or a related quantitative field., 6-9 years of experience in data or analytics engineering., Proven ability to write clean, performant, and maintainable Python for data engineering, with proficiency in libraries like Polars, Pandas and Numpy., Extensive hands-on experience with large-scale distributed systems, including dbt, Airflow, Spark, and Snowflake, Snowflake Cortex Agents., A background in building and managing complex data models and warehouses, with experience across both SQL and NoSQL databases., Experience implementing and managing frameworks for data quality testing, observability, and alerting., Solid experience with modern software development workflows, including Git, CI/CD, and Docker, to automate analytics processes., Experience mentoring other engineers and leading technical projects.
Nice to Have
Experience with pharmaceutical data and a track record of delivering business impact in the commercial pharma sector., Experience with performance tuning, cost optimization, and managing large-scale data infrastructure., Experience building dashboards using tools like Tableau, Power BI, or Streamlit., The ability to explain data limitations and how they affect business questions to non-technical audiences., Familiarity with the principles of managing data as a product.
What You'll Do.
Leads the development of core data components for our advanced analytics layer and agentic data layers.
Designs and builds end-to-end data pipelines and products specifically to power advanced AI and Retrieval-Augmented Generation (RAG) applications.
reliable data foundation that enables the use of statistical analysis
and AI models like RAG.
Implements and adheres to best practices in data management
How You'll Work.
Team & Collaboration
Collaborating closely with subject matter experts and data scientists.; Works closely with cross-functional teams to help execute the enterprise Data Strategy.; Exhibits effective communication skills for workplace interactions, including conveying ideas clearly and listening actively.
Communication Scope
Effective communication skills for workplace interactions, including conveying ideas clearly and listening actively.; The ability to explain data limitations and how they affect business questions to non-technical audiences.
Process & Methodology
Leading technical projects.
Full Job Description
**ROLE SUMMARY** The Global Commercial Analytics (GCA) team within the organization is dedicated to transforming data into actionable intelligence, enabling the business to remain competitive and innovative in a data-driven world. As a Manager, Data Engineer, you will play a pivotal, hands-on role creating the data solutions that fuel our most advanced AI and analytics applications. By collaborating closely with subject matter experts and data scientists, you will develop the robust data models, pipelines, and feature stores required to power everything from statistical analysis to complex AI and machine learning models. Your primary mission is to build the data foundation for high-impact projects such as ROI analysis, DT, Field Force sizing, On demand analytics, Data Strategy, Multi-Agents. You will be central to delivering new, innovative capabilities by enabling the deployment of cutting-edge AI and machine learning algorithms, directly helping the business solve its most challenging problems and create value. This is a dynamic, fast-paced, and highly collaborative role, covering a broad range of strategic topics critical to the pharma business. **ROLES & RESPONSIBILITIES ** **• Advanced Layer Development** : Leads the development of core data components for our advanced analytics layer and agentic data layers, enabling next-generation analytics and AI tools. **• Data Strategy Execution** : Works closely with cross-functional teams to help execute the enterprise Data Strategy, translating roadmaps into technical designs and building solutions using standard technology stacks. **• Building AI & RAG Pipelines**: Designs and builds end-to-end data pipelines and products specifically to power advanced AI and Retrieval-Augmented Generation (RAG) applications for the Commercial Pharma domain. **• Enabling Advanced Analytics** : Builds the clean, reliable data foundation that enables the use of statistical analysis, machine learning, and AI models like RAG to uncover pa
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