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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, Data Integration Engineer - **Company:** Pfizer Inc. - **Location:** Charleston, WV, United States - **Experience:** Expert - **Salary:** $176,600.0 - $294,300.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Integration Architecture, Databases, Continuous Integration, Data Dictionary, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Masking, Data Profiling, Data Security, Data Structures, Graph Database, Machine Learning, Meta-Data Management, Salesforce.Com, SQL Databases, Systems Integration, Large Language Models, Snowflake, Backend, Data Strategy, Build Management, Information Technology, No-code Tools, Data Analytics, Low-code, Graphql, Data Management, Machine Learning Operations, Virtual Agents, Data Delivery, Api Design, Api Gateway, Data Pipelines, Marketing Cloud, GXP - **Published:** September 20, 2026 - **Apply:** https://dejobs.org/x/x/86FD20BAC3A44714AE0EF54B218B3006/job/ ## About the Role Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact. * 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., * Experience in pharmaceutical, life sciences, or another regulated industry; Medical Affairs or commercial life sciences data experience a significant plus. * Experience with API gateway/middleware technologies and event-streaming platforms for real-time application integration. * Advanced degree in a technical field. Non-Standard Work Schedule, Travel, or Environment Requirements * Must be able to travel to Pfizer offices, vendor offices, and other team meeting locations when required. * Project work can sometimes be demanding and require work during off-hours to coordinate with global stakeholders or respond to data or production incidents. ## Description This role owns data integration engineering for the Medical Affairs AI Acceleration portfolio. It ensures all solutions are integrated successfully to source data. Working as an individual-contributor technical expert within the Engineering organization, this role is directly accountable for the data pipelines and integration patterns that connect Medical Affairs AI solutions to existing enterprise data sources and analytic platforms. It ensures each new AI capability has reliable, well-governed access to the data it needs without duplicating or re-architecting the underlying data platforms. This is a hands-on engineering role that develops integration software to be leveraged in any Medical Affairs AI solution. The role partners closely with Solution Architecture to implement the data integration standards and RAG/vector-database patterns defined at the architecture level, and serves as the go-to data engineering expert for Product Management and UX/Experience Design partners seeking to understand what data is available, where it lives, and how reliably it can be surfaced. The Director, Data Integration Engineer owns the design, build, and operation of the data pipelines and integration layer that connect Medical Affairs' AI-enabled products and platforms to existing data sources. Reporting to the Senior Director, Engineering, this role translates solution architecture and product requirements into reliable, governed, production-grade data pipelines that are leveraged in solutions the team is delivering for Medical Affairs. This is a technical, hands-on role responsible for designing the integration and data-access patterns for each AI solution and building, testing and operating them. This role partners closely with Build Engineers, Solution Architecture, and Product Management to ensure data readiness keeps pace with AI delivery., Data Integration Architecture & Pipeline Engineering * 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. AI & Data Enablement * Partner with Solution Architecture to implement data integration patterns supporting RAG pipelines, vector databases, GraphRAG (graph-structured retrieval context for LLMs), and other AI/ML data access patterns. * Ensure data feeding Agentic AI and LLM-based systems is well-governed, accurately labeled, and monitored for quality and drift. * Apply automation techniques (AI/ML, low-code/no-code tooling where appropriate) to accelerate data delivery. * Support context-aware and context-driven AI models by ensuring underlying data structures capture the necessary business context. Data Governance, Quality & Compliance * Collaborate and partner with the centralized Commercial AI Data Strategy team to align on data profiling, sourcing and investigation. * Apply data governance and data cataloging best practices, maintaining data dictionaries, lineage documentation, and playbooks. * Ensure data integration practice complies with Pfizer data privacy and regulatory standards (GDPR, HIPAA, GxP as applicable). * Own identification and classification of personal information (PI/PII) flowing through integration pipelines, and apply masking, tokenization, or de-identification before sensitive data is stored in a vector database or made accessible to AI/ML systems. Cross-Functional Partnership & Delivery * Partner with the Senior Director, Engineering and Build Engineers to ensure data pipelines are delivered in step with product and platform build cycles. * Partner with Solution Architecture to ensure data integration design aligns with enterprise architectural standards and reuse patterns. Continuous Improvement * Drive best practices and world-class data engineering capability, staying current with modern data platform technology (e.g., Snowflake, graph databases) and AI-enabled data tooling. * Establish a culture of high performance, transparency, and continuous improvement within the data integration discipline., Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider's name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Meet Your New BFF: Backend to Frontend without the Duct Tape](https://www.wearedevelopers.com/videos/682-meet-your-new-bff-backend-to-frontend-without-the-duct-tape) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [GraphQL + Apollo + Next.js: A Lovely Trio](https://www.wearedevelopers.com/videos/311-graphql-apollo-next-js-a-lovely-trio) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)