Senior Manager, Data Solutions Engineering

The Data Engineering team within the AI, Data, and Analytics (AIDA) organization is the backbone of our data-driven sales and marketing operations. We provide the essential foundation for transformative insights and data innovation. By focusing on integration, curation, quality, and data expertise across diverse sources, we power world-class solutions that advance Pfizer’s mission. Join us in shaping a data-driven organization that makes a meaningful global impact.

Role Summary

We are seeking a technically adept and experienced Data Solutions Engineering Senior Manager who is passionate about and skilled in designing and developing robust, scalable data models. This role focuses on optimizing the consumption of data sources to generate unique insights from Pfizer’s extensive data ecosystems. A strong technical design and development background is essential to ensure effective collaboration with engineering and developer team members.

As a Senior Data Solutions Engineer in our data lake/data warehousing team, you will play a crucial role in designing and building data pipelines and processes that support data transformation, workload management, data structures, dependencies, and metadata management. Your expertise will be pivotal in creating and maintaining the data capabilities that enables advanced analytics and data-driven decision-making.

In this role, you will work closely with stakeholders to understand their needs and collaborate with them to create end-to-end data solutions. This process starts with designing data models and pipelines and establishing robust CI/CD procedures. You will work with complex and advanced data environments, design and implement the right architecture to build reusable data products and solutions, and support various analytics use cases, including business reporting, production data pipelines, machine learning, optimization models, statistical models, and simulations.

As the Data Solutions Engineering Senior Manager, you will develop sound data quality and integrity standards and controls. You will enable data engineering communities with standard protocols to validate and cleanse data, resolve data anomalies, implement data quality checks, and conduct system integration testing (SIT) and user acceptance testing (UAT).

The ideal candidate is a passionate and results-oriented product lead with a proven track record of delivering data-driven solutions for the pharmaceutical industry.  

Role Responsibilities

• Project solutioning, including scoping, and estimation.

• Data sourcing, investigation, and profiling.

• Prototyping and design thinking.

• Designing and developing data pipelines & complex data workflows.

• Create standard procedures to ensure efficient CI/CD.

• Responsible for project documentation and playbook, including but not limited to physical models, conceptual models, data dictionaries and data cataloging.

• Technical issue debugging and resolutions.

• Accountable for engineering development of both internal and external facing data solutions by conforming to EDSE and Digital technology standards.

• Partner with internal / external partners to design, build and deliver best in class data products globally to improve the quality of our customer analytics and insights and the growth of commercial in its role in helping patients.

• Demonstrate outstanding collaboration and operational excellence.

• Drive best practices and world-class product capabilities.

Qualifications

• Bachelor’s degree in a technical area such as computer science, engineering, or management information science.  Master’s degree is preferred.

• 7+ years of combined data warehouse/data lake experience as a data lake/warehouse developer or data engineer.

• 5+ years in developing data product and data features in servicing analytics and AI use cases.

• Recent Healthcare Life Sciences (pharma preferred) and/or commercial/marketing data experience is highly preferred.

• Domain knowledge in the pharmaceutical industry preferred.

• Good knowledge of data governance and data cataloging best practices.

Technical Skillset

• 7+ years of hands-on experience in working with SQL, Python, object-oriented scripting languages (e.g. Java, C++, etc.)  in building data pipelines and processes.  Proficiency in SQL programming, including the ability to create and debug stored procedures, functions, and views.

• 7+ years of hands-on experience designing and delivering data lake/data warehousing projects.

• Minimal of 5 years in hands on design of data models.

• Proven ability to effectively assist the team in resolving technical issues.

• Proficient in working with cloud native SQL and NoSQL database platforms. Snowflake experience is desirable.

• Experience in AWS services EC2, EMR, RDS, Spark is preferred.

• Solid understanding of Scrum/Agile is preferred and working knowledge of CI/CD, GitHub MLflow.

• Familiarity with data privacy standards, governance principles, data protection, pharma industry practices/GDPR compliance is preferred.

• Great communication skills.

• Great business influencing and stakeholder management skills.

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.