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# Data Engineer Junior

- **Company:** THE JUDGE GROUP, INC.
- **Location:** Wilmington, DE, United States
- **Experience:** Starter
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Big Data, Information Engineering, Extract Transform Load (ETL), Software Debugging, Distributed Computing Environment, Python (Programming Language), Machine Learning, Cloud Services, Shell Script, Software Engineering, Data Streaming, Workflow Management Systems, Data Processing, Data Ingestion, Large Language Models, Apache Spark, Pyspark, Information Technology, Terraform, Data Pipelines, Databricks
- **Published:** June 1, 2026
- **Apply:** https://www.dice.com/job-detail/d96d6a01-7712-48d1-b24e-d98614a541cd

## About the Role

* 3+ years of hands-on experience in data engineering or related field.
 * Strong experience with Spark (PySpark preferred) and ETL/streaming pipeline development.
 * Proficiency in Python (preferred) or Java.
 * Experience with AWS cloud services such as EMR, S3, Lambda, and RDS.
 * Hands-on experience with Databricks.
 * Solid understanding of data pipelines and distributed data processing.

Preferred Qualifications (Nice to Have)

 * Experience with Airflow for workflow orchestration.
 * Proficiency in UNIX/Linux and Shell scripting.
 * Experience using Terraform for infrastructure as code.
 * Exposure to machine learning or Large Language Models (LLMs) and related use cases.

Basic Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field.

Formal training or certification in software engineering concepts.

What We're Looking For

Strong problem-solving skills and attention to detail

Hands-on experience with ETL and big data workflows

Ability to work in a fast-paced, collaborative environment

## Description

We are seeking a Junior Data Engineer to support the development and optimization of scalable data pipelines in a cloud-based environment. The role focuses on hands-on ETL development, big data processing, and contributing to critical initiatives such as Databricks migration and fraud analytics., * Design, build, and maintain scalable ETL and streaming data pipelines.

 * Develop data processing solutions using Spark (PySpark or Java).
 * Work with AWS cloud services (EMR, Lambda, S3, RDS) for data ingestion and processing.
 * Collaborate with cross-functional teams to support fraud analysis and generate actionable insights for strategy teams.
 * Contribute to Databricks migration initiatives and optimize existing workflows.
 * Perform hands-on data engineering tasks including scripting, debugging, and pipeline enhancements.


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