Senior Data Engineer

Job Description SummaryResponsible 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.

Job Description

Roles and Responsibilities

In this role, you will:
- 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
 

Education Qualification

For roles outside USA:

Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with advanced experience.

For roles in USA:Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum years of experience4years

Desired CharacteristicsTechnical 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.
Domain Expertise:
- 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
Leadership Skills:
- 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
 

Note

Note:
To comply with US immigration and other legal requirements, it is necessary to specify the minimum number of years' experience required for any role based within the USA. For roles outside of the USA, to ensure compliance with applicable legislation, the JDs should focus on the substantive level of experience required for the role and a minimum number of years should NOT be used.
This Job Description is intended to provide a high level guide to the role. However, it is not intended to amend or otherwise restrict/expand the duties required from each individual employee as set out in their respective employment contract and/or as otherwise agreed between an employee and their manager.

Additional Information