Remote PLM Data Integration Engineer

GE Aerospace; Trevose (PA); Remote; USD 112,000 - 165,000; Full time

Job summary

GE Aerospace is seeking a data engineer to map data sources, manage data movement, and build interfaces for PLM/MDM platforms. You will participate in technical discussions, design decisions, and test designs under senior guidance, contributing to reusable service-oriented components and cloud-enabled architectures.

The role emphasizes data quality at point of entry, collaboration with cross-functional teams, and exposure to ALM/PLM ecosystems, microservices, and big data tooling.

Qualifications

• Bachelor’s degree with minimum 4 years of professional experience OR Associate’s with 7+ years OR HS diploma with 9+ years of experience.
• 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 supporting data quality within PLM and MDM platforms.
• Develop, configure, and test designs for assigned components and tasks.
• Follow established enterprise architecture standards and domain governance.
• Collaborate with the business function to address data-related problems involving systems integration and product structure.
• Build peer and cross-functional relationships to share best practices.

Skills

PLM/ALM

Data mapping

SOA/microservices

Big Data

DevOps

Education

Bachelor’s degree + 4+ years

Associates degree + 7+ years

High School Diploma + 9+ years

Tools

Oracle

Elasticsearch

Solr

Hadoop

Cloud platforms

Job description

GE Aerospace is seeking a data engineer to map data sources, manage data movement, and build interfaces for PLM/MDM platforms. You will participate in technical discussions, design decisions, and test designs under senior guidance, contributing to reusable service-oriented components and cloud-enabled architectures.

The role emphasizes data quality at point of entry, collaboration with cross-functional teams, and exposure to ALM/PLM ecosystems, microservices, and big data tooling.