Director, Data Integration Engineer

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New York (NY)

On-site

USD 150,000 - 190,000

Full time

3 days ago

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Job summary

Pfizer seeks an experienced Data Integration Engineer to own end‑to‑end data pipelines for the Medical Affairs AI Acceleration portfolio. You will design patterns connecting enterprise systems to AI analytics platforms and maintain reusable ETL/ELT flows across solutions.

You will enforce coding standards, monitor latency, and implement AI data access patterns like GraphRAG and vector databases while ensuring data governance, privacy, and regulatory compliance on GDPR/HIPAA/GxP standards.

Qualifications

Bachelor's degree in Computer Science, Data Analytics, or related field.
8+ years of hands‑on data engineering or application integration experience.
Experience building data pipelines and APIs connecting applications to existing data platforms.
Advanced proficiency in SQL and hands‑on ETL/ELT pipeline development.
Experience with modern data platforms such as Snowflake, including querying and API‑based access.
Experience with API design and integration patterns, including REST/GraphQL, event‑driven, or streaming integration.
Experience with AI/ML, low‑code, or no‑code data and business process automation.
Experience supporting RAG pipelines, vector databases, or other AI/ML data access patterns.
Solid understanding of Agile delivery and CI/CD practices.
Experience identifying and protecting PI/PII using masking, tokenization, or de‑identification.
Knowledge of data governance and data cataloging best practices.

Responsibilities

Own data integration engineering for the Medical Affairs AI Acceleration portfolio.
Design and build data pipelines and integration patterns connecting enterprise systems to AI/analytics platforms.
Build and maintain reusable ETL/ELT pipelines across solutions.
Establish and follow coding standards aligned with centralized data models.
Monitor pipeline latency against timeliness thresholds.
Implement RAG pipelines, vector databases, GraphRAG, and AI/ML data access patterns.
Ensure data feeding AI systems is governed, labeled, and quality‑monitored.
Apply AI/ML and low‑code/no‑code automation to accelerate delivery.
Maintain data dictionaries, lineage documentation, and playbooks.
Ensure GDPR, HIPAA, GxP, and Pfizer data privacy standards compliance.

Skills

SQL Proficiency

ETL/ELT

Data Pipeline Design

API Development

AI/ML Automation

GraphRAG Patterns

CI/CD

Data Governance

PII Masking

Education

Bachelor's degree in CS/Data Analytics

Tools

Snowflake

REST

GraphQL

Veeva CRM

Salesforce Life Sciences

Job description

Own data integration engineering for the Medical Affairs AI Acceleration portfolio
Design and build data pipelines and integration patterns connecting enterprise systems to Medical Affairs AI and analytics platforms
Build and maintain targeted extract, transform, and serve pipelines, prioritizing reuse across solutions
Establish and follow coding standards aligned with centralized data models and cataloging practices
Monitor and manage pipeline latency against use‑case timeliness thresholds
Implement RAG pipelines, vector databases, GraphRAG, and other AI/ML data access patterns
Ensure data feeding Agentic AI and LLM systems is governed, accurately labeled, and monitored for quality and drift
Apply AI/ML and low‑code/no‑code automation to accelerate data delivery
Maintain data dictionaries, lineage documentation, and playbooks
Ensure compliance with GDPR, HIPAA, GxP, and Pfizer data privacy standards
Identify and classify PI/PII and apply masking, tokenization, or de‑identification before sensitive data reaches AI‑accessible stores
Partner with centralized Commercial AI Data Strategy, Solution Architecture, Product Management, UX/Experience Design, Build Engineers, and Engineering leadership
Deliver pipelines in step with product and platform build cycles
Drive data engineering best practices and continuous improvement

Requirements

Bachelor's degree in Computer Science, Data Analytics, or related field
8+ years of hands‑on data engineering or application integration experience
Experience building data pipelines and APIs connecting applications to existing data platforms
Advanced proficiency in SQL and hands‑on ETL/ELT pipeline development
Experience with modern data platforms such as Snowflake, including querying and API‑based access
Experience with API design and integration patterns, including REST/GraphQL, event‑driven, or streaming integration
Experience with AI/ML, low‑code, or no‑code data and business process automation
Experience supporting RAG pipelines, vector databases, or other AI/ML data access patterns
Solid understanding of Agile delivery and CI/CD practices
Experience identifying and protecting PI/PII using masking, tokenization, or de‑identification
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 GDPR, HIPAA, and GxP compliance practices
Direct experience integrating with Veeva CRM, Salesforce Life Sciences/Marketing Cloud, or other Medical Affairs systems via API
Familiarity with GraphRAG patterns
Must be able to travel to Pfizer offices, vendor offices, and other team meeting locations when required
Must be authorized to be employed in the U.S. by any employer
Permanent work authorization in the United States required
U.S. work visa sponsorship is not available now or in the future

Core Competencies

Demonstrates expertise in data integration engineering, focusing on building and maintaining data pipelines, ensuring compliance with GDPR, HIPAA, and GxP standards, and applying AI/ML automation for efficient data delivery. Proficient in collaborating with cross‑functional teams to drive data engineering best practices and continuous improvement.

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