Base: $118,000.00 to $179,035.50; bonus/equity: no...
Fully onsite
Databricks spark and delta lake
Aws s3 and cloud data platforms
Python and pyspark etl/elt development
Johnson & Johnson is seeking a Staff Data Engineer for its OTTAVA surgical robotics initiative in Santa Clara, California. The role focuses on developing data architecture and pipelines to connect manufacturing operations with cloud solutions, requiring strong technical skills in data engineering, particularly with Databricks and AWS
Job Summary
Johnson & Johnson RAD is seeking a Staff Data Engineer to drive advanced data strategies across manufacturing and supply chain operations for surgical robotics.
The role involves building scalable, reliable data pipelines and ensuring compliance with technology standards and audits to enable real-time insights and smart operations.
Employees enjoy comprehensive benefits including medical, dental, vision insurance, retirement plans, paid time off, and participation in long-term incentive programs.
Matching Summary
Match Score: 85
Johnson & Johnson is seeking a Staff Data Engineer for its OTTAVA surgical robotics initiative in Santa Clara, California. The role focuses on developing data architecture and pipelines to connect manufacturing operations with cloud solutions, requiring strong technical skills in data engineering, particularly with Databricks and AWS.
Salary
Base: $118,000.00 to $179,035.50; Bonus/Equity: Not specified; Benefits: Medical, dental, vision, life insurance, disability, retirement plans, paid time off
Skills & Requirements
Must-have
Databricks Spark and Delta Lake
AWS S3 and cloud data platforms
Python and PySpark ETL/ELT development
Data governance and quality frameworks
Integration of OT data sources
Nice-to-have
Knowledge of MedTech compliance
Real-time streaming and ML integration
Experience with ISA-95 architecture
Manufacturing and supply chain domain expertise
Strong communication and training skills
Key Requirements
Bachelor’s or Master’s in Computer Science or related field
7+ years data engineering experience (5+ for exceptional candidates)
Experience with Databricks and PySpark optimization
Knowledge of data validation and compliance (GxP, CSV)
Ability to travel up to 10% domestically/internationally