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# AWS Data Engineer Full-Time Only For USC & GC

- **Company:** Smart Caliber Technology
- **Location:** West New York, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Amazon Web Services, Amazon S3, Big Data, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Warehousing, Database Queries, DevOps, Apache Hadoop, Python (Programming Language), Machine Learning, Power BI, Tableau (Software), Enterprise Data Management, Apache Spark, Multi-Cloud, AWS Lambda, HybridCloud, Git, Cloudformation, Information Technology, AWS Glue, AWS Data Analytics, Apache Kafka, Terraform, Stream Processing, Data Pipelines, Amazon Redshift, Databricks
- **Published:** July 26, 2026
- **Apply:** https://www.careerjet.com/jobad/us5d017797833dc30a12039c7a7dd5088a

## About the Role

8+ years of experience in Data Engineering.
Strong hands-on experience with:
Amazon S3
AWS Glue
Amazon Redshift / RDS
AWS Lambda
Amazon Kinesis
Strong SQL skills.
Proficiency in Python, Scala, or Java.
Experience with ETL/ELT frameworks and data integration.
Strong understanding of data modeling, data warehousing, and big data concepts.
Experience with Apache Spark and Hadoop.
Experience with Git and CI/CD pipelines.
Preferred Skills
Apache Spark
Apache Kafka
Databricks
Terraform or AWS CloudFormation
AWS Certified Data Engineer or AWS Solutions Architect certification
Power BI or Tableau
Knowledge of data governance, security, and compliance.
Experience with machine learning data pipelines.
Exposure to multi-cloud or hybrid cloud environments.
Soft Skills
Excellent analytical and problem-solving abilities.
Strong communication and stakeholder management skills.
Attention to detail with a focus on data quality.
Ability to work effectively in Agile environments.
Education
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.

## Description

Design, develop, and maintain scalable ETL/ELT pipelines using AWS services.
Build and manage enterprise data lakes and data warehouses using Amazon S3, Redshift, and AWS Glue.
Develop and optimize batch and real-time data processing solutions.
Ensure data quality, governance, integrity, and security across enterprise data platforms.
Integrate data from multiple sources and formats.
Collaborate with business stakeholders to translate requirements into scalable technical solutions.
Monitor, troubleshoot, and optimize data workflows for performance and reliability.
Optimize AWS infrastructure for cost and performance.
Work closely with Data Scientists, BI teams, and DevOps engineers.


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