Senior Data Engineer

GE Aerospace

full-time

Posted on: 8/21/2025

Location: Massachusetts • 🇺🇸 United States

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💰 $93,000 - $124,000 per year

Senior

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

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