Director, AI-Driven Data Integration & Pipelines

Pfizer; Pennsylvania; Hybrid; USD 177,000 - 294,000; Full time

Job summary

Pfizer is seeking an experienced Data Integration Engineer for the Medical Affairs AI Acceleration portfolio. The role focuses on building robust data pipelines, integrating core systems with AI/ML platforms, and ensuring data quality and governance.

You will partner with architecture and engineering teams to implement scalable integration patterns, manage data latency, and align with regulatory standards like GDPR/HIPAA/GxP where applicable.

Qualifications

• Bachelor's degree in Computer Science, Data Analytics or related field.
• 8+ years of hands-on data engineering or application integration experience.
• Advanced proficiency in SQL and ETL/ELT pipelines.
• Experience with Snowflake, API-based access, and data governance frameworks.
• Experience with API design and integration patterns (REST/GraphQL).
• Experience with AI/ML data access patterns (RAG, vector DBs).
• Solid understanding of Agile delivery and CI/CD practice.
• Experience identifying and protecting PI/PII in data pipelines.

Responsibilities

• Design and build data pipelines and integration patterns connecting core enterprise systems to Medical Affairs' AI and analytics platforms and data sources.
• Build and maintain targeted data pipelines for AI solutions, prioritizing reuse across solutions.
• Establish and follow data pipeline coding standards aligned with centralized data models and catalogs.
• Monitor and manage data pipeline latency to meet timeliness thresholds.

Skills

Leadership experience

Stakeholder management

Excellent communication

Data governance knowledge

Regulatory compliance awareness

Veeva Salesforce integration

Education

Bachelor's degree in Computer Science, Data Analytics or related field

Tools

Snowflake

Graph databases

APIs (REST/GraphQL)

Job description

Pfizer is seeking an experienced Data Integration Engineer for the Medical Affairs AI Acceleration portfolio. The role focuses on building robust data pipelines, integrating core systems with AI/ML platforms, and ensuring data quality and governance.

You will partner with architecture and engineering teams to implement scalable integration patterns, manage data latency, and align with regulatory standards like GDPR/HIPAA/GxP where applicable.