Data Engineer

GE Aerospace•Arkansas City, KS

9d•Onsite

About The Position

Responsible for developing, testing and implementing data engineering solutions to generate analytical and reporting solutions. Responsible for analyzing and preparing the data needed for data science based outcomes. Also responsible for managing and maintaining metadata data structures besides providing necessary support for post-deployment related activities when needed.

Requirements

Bachelor’s degree from accredited university or college with minimum of 1 years of professional experience OR Associates degree with minimum of 4 years of professional experience OR High School Diploma with minimum of 6 years of professional experience
Military experience is equivalent to professional experience
Legal authorization to work in the U.S. is required.
Ability to be on-site for the role to support customers.

Nice To Haves

Ability to understand logical and physical data models, big data storage architecture, data modeling methodologies, metadata management, master data management & data lineage techniques
Hands-on experience in programming languages like Java, Python or Scala
Hands-on experience in writing SQL scripts for Oracle, MySQL, PostgreSQL or Hive
Experience in handling both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) data models
Experience in Excel’s modern analytics suite, specifically data modeling via Power Query and structured reporting through Pivot Tables
Experience with Big Data / Hadoop / Spark / Hive / NoSQL database engines (i.e. Cassandra or HBase)
Exposure to unstructured datasets and ability to handle XML, JSON file formats
Exposure to Extract, Transform & Load (ETL) tools like Informatica or Talend
Exposure to handling machine or sensor datasets from industrial businesses
Knowledge of for industrial applications in a commercial/finance/industrial/manufacturing settings.
Exposure to finance and accounting data domains

Responsibilities

Leverage technical data dictionaries and business glossaries to analyze the datasets
Perform data profiling and data analysis for any source systems and the target data repositories
Understand metadata and the underlying data structures needed to standardize the data load processes.
Develop data mapping specifications based on the results of data analysis and functional requirements
Perform a variety of data loads & data transformations using multiple tools and technologies.
Build automated Extract, Transform & Load (ETL) jobs based on data mapping specifications
Validate the data mapping results and match with the expected results
Implement Data Quality (DQ) rules provided
Design, develop, implement, and support Spotfire reporting dashboards.
Daily maintenance support of dashboards
Partner with other team members to understand the project objectives and resolve technical issues.
Communicate project status or challenges in a clear and concise manner to the cross team members.