AI Data Integration Architect — Pipelines & Governance

Pfizer Belgium; Raleigh (NC); Hybrid; USD 177,000 - 294,000; Full time

Job summary

Pfizer is seeking a hands-on Data Integration Engineer to design and operate data pipelines that connect Medical Affairs AI platforms to enterprise data sources. You will implement governance, quality controls, and scalable integration patterns in collaboration with architecture and product teams.

The role emphasizes delivering reliable, governed data for AI enablement, with a focus on RAG pipelines, vector databases, and compliant data handling in a hybrid work environment.

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 AI/ML data access patterns including RAG and vector databases.
• Knowledge of data governance and cataloging best practices.
• Familiarity with pharma data privacy standards (GDPR/HIPAA) and compliance.

Responsibilities

• Design and build data pipelines and integration patterns connecting core enterprise systems to Medical Affairs' AI and analytics platforms.
• Build and maintain targeted data pipelines that extract, transform, and serve data for each AI solution.
• Monitor data pipeline latency and ensure timely data delivery for use cases.
• Collaborate with Solution Architecture to implement RAG, vector databases, and GraphRAG patterns.

Skills

SQL

API design

Agile delivery

CI/CD

GraphRAG

Data governance

PII masking

Stakeholder mgmt

Education

Bachelor's in CS/Data Analytics

Tools

Snowflake

Graph databases

API gateway

Veeva CRM

Salesforce LCS

GraphRAG

Job description

Pfizer is seeking a hands-on Data Integration Engineer to design and operate data pipelines that connect Medical Affairs AI platforms to enterprise data sources. You will implement governance, quality controls, and scalable integration patterns in collaboration with architecture and product teams.

The role emphasizes delivering reliable, governed data for AI enablement, with a focus on RAG pipelines, vector databases, and compliant data handling in a hybrid work environment.