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# Data Engineer

- **Company:** The Judge Group
- **Location:** Fairview, NJ, United States
- **Experience:** Expert
- **Contract:** Temporary to permanent
- **Skills:** Java (Programming Language), Agile Methodology, Airflow, Amazon Web Services, Amazon S3, JIRA, Continuous Integration, Information Engineering, Data Migration, Data Systems, Data Warehousing, Identity and Access Management, JSON, Python (Programming Language), Cloud Services, Shell Script, Parquet, Test-Driven Development (TDD), Apache Spark, HybridCloud, Git, Pyspark, Solid Principles, Kubernetes, Avro, Data Management, Restful APIs, Data Pipelines, Jenkins
- **Published:** October 9, 2026
- **Apply:** https://www.disabledperson.com/jobs/75856661-data-engineer

## About the Role

* Strong proficiency in Python and/or Java with Spark/PySpark.
 * Experience with Data Pipelines, Data Modeling, Data Warehousing, and Data Migration.
 * Hands-on experience with AWS (Glue, EMR, S3, Athena, Kinesis/MSK, Airflow, Lambda, Step Functions, Lake Formation).
 * Knowledge of Kubernetes, CI/CD, Agile methodologies, and software design principles.
 * Experience with data formats such as Parquet, Iceberg, Avro, or JSON.
 * Understanding of AWS security concepts including IAM, KMS, Encryption, and Secrets Manager.

Preferred Qualifications

 * Experience building REST APIs using Java.
 * Knowledge of Hybrid Cloud architectures.
 * Exposure to Jenkins, Git, Linux Scripting, JIRA, and TDD.
 * Strong leadership, problem-solving, and communication skills.

## Description

We are seeking a Lead Software Engineer - Data Engineering to design and build scalable, cloud-native data platforms and pipelines. You will lead the development of robust data solutions, drive architectural decisions, and mentor engineers while ensuring reliability, security, and operational excellence., * Design and develop large-scale data pipelines and data platforms.

 * Build cloud-native solutions using AWS services and Spark.
 * Lead data modeling, warehousing, migration, and analytics initiatives.
 * Improve system performance, resilience, monitoring, and automation.
 * Collaborate with cross-functional teams and mentor junior engineers.