J

Johnson & Johnson

Makes prescription drugs and medical devices

Principal Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNew Brunswick, NJ, USA$102k - $170kRemote

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field is required; a master's degree is preferred.
  • At least 15 years of experience in enterprise data engineering, technical architecture, analytics, AI platforms, and cloud engineering.
  • Proven experience leading architecture decisions, technical strategy, and engineering standards across multiple teams and products.
  • Hands-on expertise 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 disciplines.
  • Demonstrated expertise with Generative AI technologies, including large language models, retrieval-augmented generation, 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 supporting enterprise AI and intelligent automation.
  • Experience leading the selection, implementation, integration, and operation of enterprise data, analytics, AI, and digital platforms.
  • Strong experience managing products and platforms throughout their lifecycle in complex, multi-team environments.
  • Deep understanding of enterprise delivery practices, including planning, dependency management, governance, compliance, quality management, and operational excellence.
  • Ability to align technology investments with business strategy, value drivers, and industry trends.
  • Strong understanding of cloud-native architectures, API-first design, distributed systems, and enterprise integration patterns.
  • Expertise with modern software development lifecycle practices, continuous integration and continuous delivery pipelines, test automation, DevOps, containerization, Infrastructure as Code, and platform engineering.
  • Exceptional communication, collaboration, and stakeholder management skills to influence technical and non-technical audiences.
  • Proven ability to lead through ambiguity and drive alignment across business and technology organizations.

Responsibilities

  • Lead the end-to-end data integration strategy for the Butterfly program, ensuring seamless data movement across customer relationship management, enterprise resource planning, master data management, customer data platforms, analytics, and downstream platforms.
  • Own integration architecture decisions, standards, and patterns across batch, real-time, API-based, event-driven, and file-based integrations.
  • Partner with business, product, and application teams to define data exchange requirements and align with enterprise data standards.
  • Drive the design, development, testing, and deployment of scalable integration solutions supporting global releases and country rollouts.
  • Establish and govern integration design reviews, technical specifications, mapping documents, and interface contracts.
  • Coordinate cross-functional teams to manage integration dependencies, risks, and release readiness.
  • Serve as the primary technical lead for application onboarding, source-to-target mapping, integration assessments, and data flow design.
  • Ensure integration solutions meet performance, reliability, scalability, security, and compliance requirements.
  • Design and implement enterprise integration solutions using APIs, ETL/ELT pipelines, messaging frameworks, event-driven architectures, and cloud-native integration patterns.
  • Lead source system onboarding and integration of commercial, customer, product, consent, and transactional data into Butterfly data products.
  • Establish reusable integration frameworks, canonical data models, and standardized mapping approaches to accelerate delivery and reduce complexity.
  • Embed data quality controls, reconciliation processes, exception handling, and monitoring capabilities into all integration solutions.
  • Collaborate with master data management, Data Product, Analytics, Experience, and Application teams to support a unified enterprise data ecosystem.
  • Define integration observability standards, including logging, alerting, monitoring, service-level agreement management, and operational support processes.
  • Drive API-first integration strategies and support the governance and lifecycle management of enterprise APIs and data services.
  • Lead migration and modernization efforts from legacy integrations to cloud-native architectures leveraging Azure, Databricks, and Microsoft Fabric.
  • Lead and influence technical teams across multiple squads, functions, geographies, and experience levels.
  • Coach, develop, and mentor engineering talent while promoting accountability, ownership, and innovation.
  • Establish trusted partnerships with architects, engineering leaders, product leaders, and business stakeholders.

Desired Qualifications

  • Experience operating in highly regulated industries with stringent security, privacy, compliance, and quality requirements.
  • Experience partnering with Information Security Risk Management, Quality & Compliance organizations, and audit functions to ensure operational readiness and control compliance.
  • Experience with enterprise knowledge management platforms, document intelligence solutions, and semantic technologies.
  • Familiarity with knowledge graphs, graph databases, vector platforms, enterprise search, and advanced AI retrieval strategies.
  • Demonstrated experience establishing engineering observability, reliability engineering practices, Site Reliability Engineering, and operational excellence frameworks.
  • Experience driving measurable business outcomes and value realization through enterprise data and AI initiatives.
  • Experience leading enterprise AI transformation programs, AI platform strategy, and adoption of emerging AI technologies at scale.

About the Company

Johnson & Johnson

Makes prescription drugs and medical devices

Johnson & Johnson develops prescription medicines and makes medical devices for hospitals, and unlike most big drugmakers, it runs both businesses under one roof. In 2015, its Darzalex became the first antibody drug approved for multiple myeloma, a blood cancer. Its medicines treat cancer, immune diseases such as psoriasis, and mental illnesses such as depression, and patented drugs bring in most of its sales. Its MedTech unit makes heart pumps, catheters that treat irregular heartbeats, surgical sutures, and Acuvue contact lenses. It was founded in 1886 to make sterile surgical dressings, is based in New Brunswick, New Jersey, and spun off its consumer brands, such as Tylenol and Band-Aid, as Kenvue in 2023.

Company size
10,001+
Company stage
IPO
Headquarters
New Brunswick, NJ
Founded
1886

Recently Posted Jobs

Explore more opportunities at Johnson & Johnson

See more jobs