Hybrid Data Integration Lead for AI Pipelines

Pfizer Belgium

Indianapolis (IN)

Hybrid

USD 177,000 - 294,000

Full time

5 days ago

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Benefits offered by this job

Relocation assistance

Health benefits

401(k) with company match

Job summary

Pfizer is seeking an experienced Director of Data Integration Engineering to own design, build, and operation of data pipelines connecting Medical Affairs AI solutions to enterprise data sources. This hands-on role partners with Solution Architecture to implement data integration standards and will drive governance, quality, and timely data delivery for AI-enabled products.

The candidate will lead integration patterns, support RAG pipelines and vector databases, ensure PII protection, and

Qualifications

Bachelor's degree in Computer Science, Data Analytics or related field.
8+ years of hands-on data engineering or application integration experience, including building data pipelines and APIs that connect applications to existing data platforms.
Advanced proficiency in SQL and hands-on experience building ETL/ELT pipelines.
Experience consuming and integrating with modern data platform technologies (e.g., Snowflake, or equivalent), including querying, API-based access, and working within an existing data governance framework.
Experience with API design and integration patterns (REST/GraphQL, event-driven or streaming integration) for connecting applications to backend data sources.
Experience with data analytics automation and business process automation using AI, ML, low-code, or no-code tools.
Experience supporting RAG pipelines, vector databases, or other AI/ML data access patterns.
Solid understanding of Agile delivery and CI/CD practice.
Experience identifying and protecting personal information (PI/PII) in data pipelines, including applying data masking, tokenization, or de-identification techniques before sensitive data reaches AI-accessible stores such as vector databases.
Good knowledge of data governance and data cataloging best practices.
Experience partnering with engineering, architecture, and business stakeholders in a matrixed delivery model.
Excellent communication and stakeholder management skills.
Familiarity with data privacy standards and pharma industry compliance practices (GDPR, HIPAA, GxP).
Direct experience integrating with Veeva CRM, Salesforce Life Sciences/Marketing Cloud, or other Medical Affairs systems via API.
Familiarity with GraphRAG patterns - using graph-structured data to organize retrieval context for LLMs - as a complement to standard vector-based RAG.

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 that extract, transform, and serve the specific data each AI solution needs, prioritizing reuse across solutions.
Establish and follow data pipeline coding standards for solution-level integration work, aligning with the data models and cataloging practices maintained by the centralized data organization.
Monitor and manage data pipeline latency, ensuring each AI solution receives data within the timeliness thresholds its use case requires.