> Markdown version of [/jobs/ext/4584189-data-engineer](https://www.wearedevelopers.com/jobs/ext/4584189-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer

- **Company:** HAN IT STAFFING, INC.
- **Location:** Woodbridge Township, NJ, United States
- **Experience:** Expert
- **Salary:** $149,760.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Amazon S3, Batch Processing, Big Data, Cloud Computing Security, Cloud Engineering, Cloud Storage, Extract Transform Load (ETL), Data Systems, Identity and Access Management, Python (Programming Language), Performance Tuning, Query Optimization, SQL Databases, Sql Optimization, Pyspark, AWS Glue, AWS Data Analytics, Apache Kafka, Spark Streaming, Data Management, Data Pipelines, Jenkins, Databricks
- **Published:** November 5, 2026
- **Apply:** https://www.thejobnetwork.com/job/b49ec15e-1d7c-48e4-be09-4a3c1ac2ccf7/data-engineer

## About the Role

* Advanced SQL - Query tuning, performance optimization
 * AWS S3/Redshift - Strong experience with cloud storage warehouse
 * AWS Glue - ETL development, job orchestration
 * Databricks - Spark based transformations and pipelines
 * Python/PySpark - Hands on programming for large scale data processing
 * IAM & Security - Strong understanding of roles, policies, and cloud security
 * DevOps - Jenkins/GitLab CI/CD pipelines
 * Agile - Experience with Agile delivery frameworks

P Nice to Have

 * Kafka/Spark Streaming - Real time ingestion
 * DBT - Data modeling & transformations

## Description

* Data Pipelines - Build and maintain scalable ingestion and ETL pipelines on AWS.
 * AWS Data Services - Work with S3, Redshift, Glue, Lambda, and Databricks for batch processing.
 * SQL Engineering - Write optimized SQL for large datasets and analytical workloads.
 * Cloud Architecture - Design secure, high performance data solutions using IAM best practices.
 * Data Quality - Ensure accuracy, consistency, and governance across data platforms.
 * Collaboration - Work with cross functional teams in Agile environments.