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 Manager with a passion for developing data products and innovative solutions to create competitive advantages for Pfizer's commercial business units. This role requires a strong technical background to ensure effective collaboration with engineering and developer team members. As a Data Solutions Engineer in our data lake/data warehousing team, you will play a crucial role in building data pipelines and processes that support data transformation, workload management, data structures, dependencies, and metadata management.
This role will need to be able to work closely with stakeholders to understand their needs and work alongside them to ensure data being ingested meets the business user's needs and will well modeled and organized to promote scalable usage and good data hygiene . Work with complex and advanced data environments, employ the right architecture to handle data, and support various analytics use cases including business reporting, production data pipeline, machine learning, optimization models, statistical models, and simulations.
The Data Solutions Engineering Manager will ensure data quality and integrity by validating and cleansing data, identifying, and resolving anomalies, implementing data quality checks, and conducting 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.
• Developing data pipelines & complex data workflows.
• Actively contribute to project documentation and playbook, including but not limited to physical models, conceptual models, data dictionaries and data cataloging.
• 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.

• 4+ years of combined data warehouse/data lake experience as hands on data engineer.
• 2+ 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

• 4+ 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.
• 4+ years of hands-on experience delivering data lake/data warehousing projects.
• Experience 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 w orking 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.
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