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Data Engineer
Job in
Cartersville, Bartow County, Georgia, 30120, USA
Listed on 2026-08-03
Listing for:
Qcells USA Corp.
Full Time
position Listed on 2026-08-03
Job specializations:
-
IT/Tech
Data Engineering, Data Analyst
Job Description & How to Apply Below
Description
The Data Engineer will support the data pipeline operations of solar product manufacturing lines, assisting with data gathering, processing, analysis, and visualization.
SUMMARYThe Data Engineer will support the data pipeline operations of solar product manufacturing lines, assisting with data gathering, processing, analysis, and visualization.
Responsibilities- Assist in defining and extracting manufacturing data from multiple sources, and support integration into a target database, application, or file using efficient programming practices
- Support the design and development of data visualizations to convey information to engineers and technicians
- Develop and help maintain scripts for ETL process support, monitoring, and basic performance tuning
- Collaborate with cross-functional teams to help identify and resolve data quality and operational issues
- Maintain existing data pipelines and support enhancement requests for visualizations.
- Bachelor''s degree in a quantitative discipline (e.g. Computer Science, Statistics, Industrial Engineering, Management Information Systems, or a related field) with 2+ years of relevant experience
- Familiarity with relational databases such as Oracle, Microsoft SQL or MySQL
- Basic understanding of Object-Oriented Programming concepts
- Strong analytical, problem-solving, and written/verbal communication skills
- Ability to work independently and collaboratively in a team environment
- Eagerness to learn and grow within a fast-paced manufacturing environment
- Master’s degree in quantitative discipline(e.g. Computer Science, Statistics, Industrial Engineering, Electrical Engineering, Chemical Engineering or a related field)
- Exposure to the manufacturing industry, such as solar PV, display or semiconductors
- Familiarity with data visualization tools;
Spotfire, Tableau, Power BI, etc. - Exposure to big data technologies;
Hadoop, Spark, Kafka, etc. - Exposure to cloud platforms; AWS, Azure, or GCP (e.g. coursework, certifications, or personal projects)
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