Remote PLM Data Integration Engineer

GE Aerospace; Boise (ID); Remote; USD 112,000 - 165,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Paid time off

Career development

Job summary

GE Aerospace seeks a data engineering professional to map data sources, movements, and interfaces within PLM/MDM ecosystems. You will engage in technical discussions, develop and test designs, and adhere to enterprise architecture standards.

The role emphasizes service-oriented components, POCs, and collaboration across teams to ensure data quality and effective system integration. Experience with ALM/PLM, microservices, Hadoop-based ecosystems, and cloud technologies is valuable.

Qualifications

• 4+ years of professional experience or equivalent combinations as described in the Basic Qualifications.
• 3+ years of professional experience in Application Engineering.
• Military experience counts as professional experience.

Responsibilities

• Map data sources, data movement, and interfaces to support data quality in PLM/MDM platforms.
• Participate in technical discussions and document design decisions.
• Develop, configure, and test component designs.
• Follow enterprise architecture standards and governance.
• Research tools and technologies to support tasks.
• Build service-oriented platform components for reuse.
• Create POCs using established patterns under guidance.
• Collaborate with project lead to align work with goals.

Skills

Data mapping

Data movement

Interfaces

Analytics

PLM systems

SOA

DevOps

Big Data

Education

Bachelor’s degree or higher

Associates degree with 7+ years experience

High School Diploma with 9+ years experience

Tools

Hadoop

Elasticsearch

Solr

Cloud platforms

DevOps tooling

Job description

GE Aerospace seeks a data engineering professional to map data sources, movements, and interfaces within PLM/MDM ecosystems. You will engage in technical discussions, develop and test designs, and adhere to enterprise architecture standards.

The role emphasizes service-oriented components, POCs, and collaboration across teams to ensure data quality and effective system integration. Experience with ALM/PLM, microservices, Hadoop-based ecosystems, and cloud technologies is valuable.