Job description

Job Description Summary Responsible for designing, developing, testing and implementing data engineering processes 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. Expected to actively look for automation opportunities, using artificial intelligence tools where appropriate, to reduce manual work and improve process efficiency. Accountable to deliver results in a timely manner using agile methodologies Job Description Roles and Responsibilities Build technical data dictionaries and support business glossaries to analyze the datasets Perform data profiling and data analysis for source systems, manually maintained data, machine generated data and target data repositories Build both logical and physical data models for both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) solutions Develop and maintain 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 Maintain metadata structures needed for building reusable Extract, Transform & Load (ETL) components. Analyze reference datasets and familiarize with Master Data Management (MDM) tools. Analyze the impact of downstream systems and products Derive solutions and make recommendations from deep dive data analysis. Design and build Data Quality (DQ) rules needed Minimum Qualification Bachelor’s degree from accredited university or college with minimum of 2 years of professional experience OR Associates degree with minimum of 5 years of professional experience OR High School Diploma with minimum of 7 years of professional experience Note: Military experience is equivalent to professional experience Eligibility Requirement: -Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job. Desired Characteristics Technical Expertise: Exposure to industry standard data modeling tools (e.g., ERWin, ER Studio, etc.). Exposure to Extract, Transform & Load (ETL) tools like Informatica or Talend Exposure to industry standard data catalog, automated data discovery and data lineage tools (e.g., Alation, Collibra, TAMR etc., ) Hands-on experience in programming languages like Java, Python or Scala Hands-on experience in writing SQL scripts for Oracle, MySQL, PostgreSQL or HiveQL - 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 Conduct exploratory data analysis and generate visual summaries of data. Identify data quality issues proactively. This role requires access to U.S. export-controlled information. Therefore, employment will be contingent upon the ability to prove that you meet the status of a U.S. Person as one of the following: U.S. lawful permanent resident, U.S. Citizen, have been granted asylee or refugee status (i.e., a protected individual under the Immigration and Naturalization Act, 8 U.S.C. 1324b(a)(3)). Additional Information GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace 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. GE Aerospace will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Employees may also be subject to random and reasonable-suspicion drug and alcohol testing. Relocation Assistance Provided: No

Requirements

Must-haves

Job Description Summary Responsible for designing, developing, testing and implementing data engineering processes 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.
Job Description Roles and Responsibilities
Build technical data dictionaries and support business glossaries to analyze the datasets
Perform data profiling and data analysis for source systems, manually maintained data, machine generated data and target data repositories
Build both logical and physical data models for both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) solutions
Develop and maintain 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
Maintain metadata structures needed for building reusable Extract, Transform & Load (ETL) components.
Analyze reference datasets and familiarize with Master Data Management (MDM) tools.
Analyze the impact of downstream systems and products
Derive solutions and make recommendations from deep dive data analysis.
Design and build Data Quality (DQ) rules needed
Note: Military experience is equivalent to professional experience
-Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job.
Desired Characteristics
Exposure to industry standard data modeling tools (e.g., ERWin, ER Studio, etc.).
Exposure to Extract, Transform & Load (ETL) tools like Informatica or Talend
Exposure to industry standard data catalog, automated data discovery and data lineage tools (e.g., Alation, Collibra, TAMR etc., )
Hands-on experience in programming languages like Java, Python or Scala
Hands-on experience in writing SQL scripts for Oracle, MySQL, PostgreSQL or HiveQL - 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

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Keywords to mirror

agilejavapythonsql

Platform: workday
Effort: long

Benefits

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Professional Development