Remote PLM Data Integration Engineer

GE Aerospace; San Ramon (CA); Remote; USD 112,000 - 165,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Tuition assistance

Paid time off and holidays

Job summary

GE Aerospace in California seeks a data integration specialist to map data sources and movements, ensuring data quality across PLM/MDM platforms. You will implement designs, test components, and follow enterprise architecture standards under senior guidance.

Experience in ALM/PLM environments, microservices, and cloud/DevOps concepts is beneficial. A strong focus on data quality and collaborative problem-solving is essential.

Qualifications

• Bachelor’s degree or equivalent with minimum 4 years of professional experience, or Associate with 7+ years, or HS diploma with 9+ years.
• Minimum 3 years of professional experience in Application Engineering.
• Military experience is equivalent to professional experience.

Responsibilities

• Execute data mapping, data movement, and interface tasks to support data quality in PLM and MDM platforms.
• Participate in technical discussions and document design decisions.
• Develop, configure, and test designs for assigned components and tasks.
• Follow established enterprise architecture standards and governance.
• Research and evaluate tools to support project tasks.
• Contribute to service-oriented data delivery platform components.
• Build and test proofs-of-concept using established patterns under guidance.
• Collaborate with project lead to align tasks with project goals.
• Engage with business to address data-related problems involving system integration.

Skills

Data mapping

Education

Bachelor’s degree

Associate degree

High School Diploma

Job description

GE Aerospace in California seeks a data integration specialist to map data sources and movements, ensuring data quality across PLM/MDM platforms. You will implement designs, test components, and follow enterprise architecture standards under senior guidance.

Experience in ALM/PLM environments, microservices, and cloud/DevOps concepts is beneficial. A strong focus on data quality and collaborative problem-solving is essential.