Data Engineer
Hanwha Q Cells EPC USA LLC
Cartersville, United States of America
7 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Cartersville, United States of America
Tech stack
Clean Code Principles
Amazon Web Services (AWS)
Azure
Big Data
Cloud Computing
Databases
ETL
Data Visualization
Relational Databases
Hadoop
Microsoft SQL Server
MySQL
Object-Oriented Software Development
Oracle Applications
Performance Tuning
Power BI
Tableau
Technical Data Management Systems
Spark
Information Technology
Kafka
Spotfire
Data Pipelines
Job description
The Data Engineer will support the data pipeline operations of solar product manufacturing lines, assisting with data gathering, processing, analysis, and visualization., * 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.
Requirements
- 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)