GE Aerospace

Senior Data Engineer

GE Aerospace

full-time

Posted on:

Origin:  • 🇺🇸 United States • Massachusetts

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Salary

💰 $93,000 - $124,000 per year

Job Level

Senior

Tech Stack

AWSAzureCassandraCloudETLGoogle Cloud PlatformHadoopHBaseInformaticaJavaMySQLNoSQLOraclePostgresPythonSparkSQL

About the role

  • Design, implement, and maintain scalable data integration solutions across multiple systems
  • Lead data profiling, metadata and dictionary development, data modeling, and Master Data Management (MDM) support
  • Build and maintain data architectures including relational databases, graph databases and OLTP/OLAP models
  • Develop knowledge graphs and semantic layers; define ontologies and ensure schema alignment between enterprise data and graph structures
  • Integrate knowledge graph systems with structured and unstructured data sources (XML, JSON, etc.)
  • ETL/ELT: build pipelines using Informatica, Talend, or Python/Java; automate data loads and transformations
  • Maintain metadata structures to support reusable ETL components and monitor pipeline performance
  • Architect and maintain enterprise databases for operational and analytical workloads; reverse-engineer schemas and integrate legacy systems
  • Develop user interfaces, data services, and visual tools to enable data access, curation, and reporting
  • Perform root cause analysis of data issues and contribute to Data Quality (DQ) rule creation and validation
  • Build technical data dictionaries and contribute to data governance, data lineage, data cataloging, and data discovery tools

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or a STEM-related field and 3+ years of experience in data processing, applications, or software development
  • OR a high school diploma / GED with a minimum of 7 years of experience in data processing, applications, or software development
  • Preferred Experience: 5+ years of hands-on experience in data architecture, ETL development, and database design
  • Proficiency in SQL (Oracle, PostgreSQL, MySQL, HiveQL), Python, and/or Java
  • Experience with Big Data ecosystems (Hadoop, Spark, Hive, NoSQL like Cassandra or HBase)
  • Familiarity with data modeling tools (ERWin, ER/Studio)
  • Exposure to AI/ML pipelines and data requirements for training and inference
  • Experience working with cloud platforms (AWS, Azure, or GCP)
  • Ability to conduct exploratory data analysis and proactively identify data quality issues
  • Strong cross-functional collaboration skills and the ability to influence data strategy across teams
  • Excellent verbal and written communication, including technical presentations
  • Comfortable working in fast-paced, agile, and collaborative environments