Principal Data Engineer

Description

The company works in healthcare through its Innovative Medicine and MedTech businesses, aiming to prevent, treat and cure complex diseases.

This is a Principal Data Engineer role focused on AI. You will own product engineering and architecture decisions, setting the technical direction while also building and delivering solutions yourself.

You will work with Product Owners, Product Group Engineers, Lead Engineers, architects and cross-functional product squads on difficult engineering problems, scalable designs and alignment with enterprise technology strategy.

The role is accountable for product architecture, engineering standards, technology roadmaps and delivery of scalable, secure, governed data and AI solutions.

The ideal candidate has 10+ years of progressive experience in enterprise data engineering, architecture, analytics and AI.

Job function: Data Analytics & Computational Sciences. Sub-function: Data Engineering. Category: Scientific/Technology.

Responsibilities

• Set the engineering strategy, technical architecture, roadmap and direction for the product, working with Product Owners, Product Group Engineers and Business Unit Architects.
• Make sure implementations fit enterprise architecture standards, business goals, economic frameworks and long-term technology strategy.
• Work with business stakeholders to shape the product vision, define capabilities and turn business needs into scalable data, analytics and AI solutions.
• Stay hands-on by taking part in architecture, design and code reviews, and by building proofs of concept and technical enablers.
• Compare solution options, test ideas with stakeholders and make well-grounded technology choices.
• Work across product and platform teams to increase reuse, standardization and platform adoption while reducing duplicate solutions.
• Lead technical planning and governance across several squads so architecture, engineering practice, scalability and maintainability stay consistent.
• Drive modern engineering practices that improve reliability, performance, security, observability and delivery quality.
• Own the lifecycle of APIs, data interfaces, integration patterns and platform modernization.
• Track emerging technologies and trends, running innovation spikes and pilots to find business value.
• Help Product Owners and Lead Engineers prioritize the backlog and manage technical debt.
• Mentor engineers and technical leaders, building a culture of excellence, innovation, collaboration and continuous learning.
• Manage technical risks, dependencies, impediments and cross-product integration issues.
• Act as the main technical contact for ISRM, Quality and Compliance (Q-CSV), vendors, enterprise platform teams and external partners.
• Lead design and build of enterprise Generative AI and Agentic AI solutions using Azure OpenAI, Azure AI Services, Microsoft Fabric AI, Databricks AI/ML and enterprise knowledge platforms.
• Design and run scalable RAG solutions, vector databases, semantic search, knowledge graphs and document intelligence platforms.
• Build and govern AI-ready data products that give AI applications trusted, secure and contextualized data.
• Set standards for prompt engineering, model evaluation, observability, guardrails, responsible AI, performance monitoring and LLMOps/MLOps lifecycle management.
• Build scalable AI data pipelines for embeddings, vectorization, document ingestion, multimodal processing and unstructured data.
• Work with business, analytics, digital and experience teams to pick high-impact AI use cases with measurable outcomes.
• Make sure AI solutions meet enterprise security, privacy, governance, regulatory and responsible AI requirements.
• Assess new foundation models, copilots, AI agents and AI platforms, and adopt them where value can be shown.
• Lead design, build and rollout of enterprise data products, platforms and pipelines on Azure, Microsoft Fabric, Databricks and cloud-native architectures.
• Design and implement Lakehouse, Warehouse, Data Product and Data Sharing architectures for analytics and AI workloads.
• Enable governed analytics and semantic modeling in Power BI, covering performance, security, scalability and model governance.
• Apply Data Mesh principles and federated governance to support domain ownership and scalable data ecosystems.
• Set and enforce enterprise data modeling standards across conceptual, logical, physical, dimensional, canonical and domain-oriented models.
• Put data governance in place covering quality, metadata, lineage, master data integration, security and access controls.
• Build architectures for structured and unstructured data used in advanced analytics and AI.
• Enable data product use through APIs, event-driven architectures and enterprise integration patterns.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science or a related field.
• 15+ years of experience in enterprise data engineering, technical architecture, analytics, AI platforms and cloud engineering.
• Proven record of leading architecture decisions, technical strategy and engineering standards across multiple teams and products.
• Hands-on experience with Azure, Microsoft Fabric, Databricks, Power BI and modern cloud-native technologies.
• Strong experience with Data Mesh, Data Federation, Data Products, Data Modeling, Data Governance and Enterprise Data Management.
• Demonstrated expertise in Generative AI, including LLMs, RAG, vector databases, AI agents, prompt engineering and enterprise AI architectures.
• Experience implementing MLOps, LLMOps, Responsible AI, model governance and AI operationalization frameworks.
• Strong understanding of structured and unstructured data architectures that support enterprise AI and intelligent automation.
• Excellent communication, collaboration and stakeholder management skills, with the ability to influence technical and non-technical audiences.
• Proven ability to lead through ambiguity and align business and technology organizations.
• Experience leading Agile delivery, including product development, governance, standards and organizational change.
• Strong grasp of cloud-native architecture, API-first design, distributed systems and enterprise integration patterns.
• Working knowledge of modern SDLC, CI/CD, test automation, DevOps, containerization, Infrastructure as Code and platform engineering.
• Ability to weigh technical trade-offs and guide teams to scalable, maintainable solutions.
• Experience leading selection, implementation, integration and operation of enterprise data, analytics, AI and digital platforms.
• Ability to tie technology investment to business strategy, value drivers and industry trends.
• Preferred: Master's degree.
• Preferred: Experience in highly regulated industries with strict security, privacy, compliance and quality requirements.
• Preferred: Experience working with ISRM, Quality & Compliance and audit functions to keep operations ready and controls compliant.
• Preferred: Experience with enterprise knowledge management, document intelligence and semantic technologies.
• Preferred: Familiarity with knowledge graphs, graph databases, vector platforms, enterprise search and advanced retrieval strategies.
• Preferred: Experience setting up engineering observability, reliability practices, Site Reliability Engineering (SRE) and operational excellence frameworks.
• Preferred: Track record of delivering measurable business outcomes through enterprise data and AI initiatives.
• Preferred: Experience leading enterprise AI transformation programs, AI platform strategy and adoption of emerging AI at scale.
• Preferred skills: Advanced Analytics, Agility Jumps, Coaching, Critical Thinking, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Digital Fluency, Execution Focus, Hybrid Clouds, Organizing, Presentation Design, Technical Development, Technical Writing, Technologically Savvy.

Conditions

This is a duration-based role lasting 2 years.

The role can be fully remote.

The job is based in New Brunswick, New Jersey, United States of America.

The anticipated base pay range is $102,000 to $170,000.

The company provides an inclusive workplace that respects diversity and dignity, and accommodations are available during the interview process on request.

Benefits

• Medical, dental, vision, life insurance, short- and long-term disability, business accident insurance and group legal insurance, subject to plan terms.
• Pension plan and 401(k) savings plan, subject to plan terms.
• Vacation: 120 hours per calendar year.
• Sick time: 40 hours per calendar year, or 56 hours for employees who live in Washington State.
• Holiday pay: 13 days per calendar year, including floating holidays.
• Personal and family time: up to 40 hours per calendar year.
• Parental leave: 480 hours within one year of the birth, adoption or foster care placement of a child.
• Condolence leave: 30 days for an immediate family member and 5 days for an extended family member.
• Caregiver leave: 10 days.
• Volunteer leave: 4 days.
• Military spouse time off: 80 hours.
• Eligibility depends on plan terms and date of hire.