Senior Data & AI Engineer - Enterprise Platforms

Johnson & Johnson; Raritan (NJ); On-site; USD 94,000 - 152,000; Full time

Benefits offered by this job

Vacation time

Sick time

Holiday pay

Parental Leave

Bereavement Leave

Volunteer Leave

Military Spouse Leave

Job summary

Johnson & Johnson is seeking a Senior Data & Applied AI Engineer to design, build, and scale enterprise data products and AI platforms. Location flexible within North America or LATAM, with a focus on data engineering, MLOps, and cloud-native architectures.

You will lead the development of data pipelines and AI-enabled services while applying modern tools like Databricks, Azure Data Factory, and Kubernetes to deliver secure, scalable enterprise solutions.

Qualifications

• Bachelor's or Master's in CS/Engineering/Data Science or related field.
• 6+ years of engineering experience delivering enterprise-scale data/AI platforms.
• Strong Python, PySpark, SQL skills and distributed data processing knowledge.
• Hands-on with Databricks, Azure Data Factory, data lake/lakehouse architectures, Azure cloud services.

Responsibilities

• Design and optimize scalable batch and streaming data pipelines.
• Develop reusable data products and analytical datasets for enterprise reporting and AI use cases.
• Design and implement AI/Generative AI solutions and MLOps capabilities for deployment and governance.
• Build cloud-native services, REST APIs, and full-stack components to operationalize data/AI solutions.
• Mentor engineers and drive engineering standards for scalable, secure, and compliant platforms.

Skills

Python

PySpark

SQL

Databricks

Azure Data Factory

MLOps

Cloud-native

APIs

TypeScript

React

Node.js

CI/CD

GitOps

RBAC

Education

Bachelor's or Master's degree in Computer Science/Engineering/Data Science

Tools

Databricks

Azure Data Factory

Azure cloud services

Docker

Kubernetes

Azure Kubernetes Service

Job description

Johnson & Johnson is seeking a Senior Data & Applied AI Engineer to design, build, and scale enterprise data products and AI platforms. Location flexible within North America or LATAM, with a focus on data engineering, MLOps, and cloud-native architectures.

You will lead the development of data pipelines and AI-enabled services while applying modern tools like Databricks, Azure Data Factory, and Kubernetes to deliver secure, scalable enterprise solutions.