Associate Data Engineer – Solar Manufacturing Pipelines

Qcells Georgia, Inc.

Cartersville (GA)

On-site

USD 90,000 - 120,000

Full time

13 days ago
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Job summary

Qcells Georgia, Inc. is seeking an EIS Associate Developer to build and operate a data pipeline for the solar product manufacturing line and perform end-to-end analysis from data gathering through visualization.

The role requires extracting data from multiple sources, creating efficient ETL processes, developing visualizations for engineers and technicians, and collaborating with cross-functional teams to ensure data quality and operational reliability.

Qualifications

  • Bachelor’s degree in Computer Science, Statistics, Industrial Engineering, MIS, or related field.
  • 3+ years of data engineer experience with multiple data sources (Oracle, SQL).
  • Experience with Java, Spring Boot, and web applications.
  • Strong understanding of OOP concepts and data pipelines.

Responsibilities

  • Define and extract high-volume manufacturing data from multiple sources and integrate into a target data store.
  • Design and develop data visualizations for engineers and technicians.
  • Develop ETL scripts for maintenance, monitoring, and performance tuning.
  • Collaborate with cross-functional teams to resolve data quality and operational issues.
  • Maintain and enhance existing data pipelines and visualizations.

Skills

OOP concepts
Analytical thinking
Communication skills

Education

Bachelor’s degree in Computer Science, Statistics, MIS or related field
Master’s degree in quantitative discipline

Tools

Java
Spring Boot
Spotfire
Tableau
PowerBI
Numpy
Scipy
Scikit-learn
Django
Flask
Hadoop
Spark
Kafka

Job description

Qcells Georgia, Inc. is seeking an EIS Associate Developer to build and operate a data pipeline for the solar product manufacturing line and perform end-to-end analysis from data gathering through visualization.

The role requires extracting data from multiple sources, creating efficient ETL processes, developing visualizations for engineers and technicians, and collaborating with cross-functional teams to ensure data quality and operational reliability.

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