GE is the world's Digital Industrial Company, transforming industry with software-defined machines and solutions that are connected, responsive and predictive. Through our people, leadership development, services, technology and scale, GE delivers better outcomes for global customers by speaking the language of industry. GE offers a great work environment, professional development, challenging careers, and competitive compensation. GE is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
The Data Engineering team helps solve our customers' toughest challenges; making flights safer, power cheaper, and oil & gas production safer for people and the environment by leveraging data and analytics. The Sr Data Engineer will work with the team to create state-of-the-art data and analytics driven solutions, working across GE to drive business analytics to a new level of predictive analytics while leveraging big data tools and technologies.
The Staff Data Engineer will be part of a data engineering or cross-disciplinary team on internally and commercially-facing development projects, typically involving large, complex data sets. These teams typically include statisticians, computer scientists, software developers, engineers, product managers, and end users, working in concert with partners in GE business units. Potential application areas include remote monitoring and diagnostics across infrastructure and industrial sectors, financial portfolio risk assessment, and operations optimization. The Sr Data Engineer will be responsible for all aspects of data acquisition, data transformation, and analytics scheduling and operationalization to drive high-visibility, cross-division Aviation outcomes. In addition, the Sr Data Engineer will:
Acquire domain Subject Matter Expertise (Supply Chain, Engineering, etc.) across IT systems by working closely with business partners, documenting learnings centrally
Write complex SQL (100’s of lines) that is able to transform, pivot, and stitch big data sets, both relational and non-relational
Write custom scripts in Python, Java, R or Spark to transform and pivot data
Integrate domain data knowledge into development of data requirements
Look across multiple systems and understand the purpose of each system and define data requirements by system
Identify downstream implications of data loads/migration (e.g., data quality, regulatory, etc.)
Develop automated testing for code deployment
Write data ingestion flows using message queuing
Operationalize and scale data science algorithms to extremely large datasets
Optimize existing data architectures and queries to scale across terabytes of data for visualization or application consumption
Architect and model to-be data structures based on customer requirements
Operate in Agile framework, creating user stories from and tasks from customer requirements to track project progress
Bachelor's Degree in Computer Science, Information Technology or equivalent (STEM) with minimum 3 years of experience as data engineer
A minimum of 1 year of experience using Hadoop ecosystem (Spark, Hive, HDFS, etc.)
A minimum of 1 year of experience working on relational SQL databases (PostgreSQL, Oracle, etc.)
Legal authorization to work in the U.S. is required. GE may agree to sponsor an individual for an employment visa now or in the future if there is a shortage of individuals with particular skills.
Demonstrated experience working in a large-scale, MPP/OLAP data warehouse environment (Greenplum, Teradata, etc.
Hands-on experience with NoSQL data architectures (Cassandra, MongoDB, HBase, etc.)
Demonstrated experience using Data Analytics languages (R, Python and associated statistical packages)
Demonstrated experience using Scripting languages (Pig, *Nix Shell, Perl, etc.)
Experience with Agile project delivery frameworks
Hands-on experience with streaming data architecture (Spark Streaming, message queues, etc.)
Exposure to and ability to execute analytics packages at scale in Python, R, Spark/MLlib
Familiarity with Hadoop data flow tools (Sqoop, Flume, Nifi, etc.)
Familiarity with Hadoop workflow tools such as Oozie
Experience with enterprise data visualization technologies (Tibco Spotfire, Tableau, etc.)
Experience with Amazon Web Services data technologies (RDS, Kinesis, QuickSight, etc.)
Familiarity with text search and mining technologies (Solr, ElasticSearch, Lucene, etc.)
Excellent written and verbal communication skills, especially with product owners
Self-driven to learn new technology and build technical skill sets
Demonstrates the initiative to explore alternate technology and approaches to solving problems
Skilled in breaking down problems, documenting problem statements and estimating efforts
Has the ability to analyze impact of technology choices
Skilled in balancing value propositions for competing stakeholders.
We are in the process of transitioning to an improved job application system and in the interim we are operating with two systems. Have your Job ID ready (from the email you received when you applied) to log in and check your application status.
Click the appropriate button. If you don't know your job ID, you can still check your status: use both buttons.