Director, AI Data Integration & Pipelines

Pfizer Belgium; Tallahassee (FL); Hybrid; USD 177,000 - 294,000; Full time

Benefits offered by this job

401(k) Matching

Health benefits

Paid vacation

Job summary

Pfizer in the United States is seeking a Data Integration Engineer to own the data pipelines and integration patterns that connect Medical Affairs AI-enabled products to enterprise data sources. This hands-on role partners with Solution Architecture to implement RAG, vector databases, and governance practices, ensuring data readiness for AI delivery.

Reporting to engineering leadership, you will design, build, test, and operate production-grade data pipelines, collaborating across product

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 or equivalent data platforms.
• Experience with API design and integration patterns (REST/GraphQL).
• Experience with RAG pipelines, vector databases, and AI data access.

Responsibilities

• Design and build data pipelines and integration patterns across core enterprise systems.
• Build and maintain reusable data pipelines for AI solutions.
• Apply data governance, cataloging, and privacy practices in pipelines.
• Collaborate with architecture, product management, and Build Engineers to deliver on timelines.

Skills

SQL

ETL/ELT pipelines

Data integration

REST/GraphQL APIs

CI/CD

Agile methodology

Data governance

Veeva/Salesforce integration

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

Graph databases

API design (REST/GraphQL)

Veeva/Salesforce integration

Job description

Pfizer in the United States is seeking a Data Integration Engineer to own the data pipelines and integration patterns that connect Medical Affairs AI-enabled products to enterprise data sources. This hands-on role partners with Solution Architecture to implement RAG, vector databases, and governance practices, ensuring data readiness for AI delivery.

Reporting to engineering leadership, you will design, build, test, and operate production-grade data pipelines, collaborating across product