Sr Data Engineer

About the position

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. Accountable to deliver results in a timely manner using agile methodologies.

Responsibilities

• Support data engineering activities in Cost as a Technology team for multiple products in the team including Prodigy
• 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

Requirements

• 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
• 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.

Nice-to-haves

• 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.
• 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
• Ability to work effectively with multi-disciplinary teams (e.g., UX, GE Business teams) and understand the inter-dependencies between them.
• Ability to showcase teamwork skills to achieve common goals, provide resolutions and share ideas.
• Demonstrate the presentation and influencing skills

Benefits

• Great work environment
• Professional development
• Challenging careers
• Competitive compensation
• Relocation Assistance Provided