Sr. AWS Data Engineer

Overview

Remote
Depends on Experience
Contract - W2
Contract - Independent

Skills

Data Engineering
Extract
Transform
Load
ETL
Amazon Web Services
AWS
Glue
Lambda
DMS
Redshift
EMR
Red Hat Linux
shell scripting
Python
SQL
data warehouse
data lake
DevOps

Job Details

We are seeking a highly skilled AWS Data Engineer with a strong background in Red Hat Linux and expertise in building ETL pipelines to support cloud data migration initiatives. The ideal candidate will have hands-on experience with AWS Migration Services and will play a critical role in designing, developing, and maintaining scalable data integration solutions in a secure and reliable cloud environment.

Key Responsibilities:

Design, build, and optimize robust ETL pipelines for data migration and integration using AWS services such as AWS Glue, Data Migration Service (DMS), Lambda, and Step Functions.

Work with AWS Migration Services to migrate on-premises data sources to AWS cloud-based data lakes and databases.

Administer and troubleshoot Red Hat Linux environments as part of the data pipeline infrastructure.

Collaborate with data architects, cloud engineers, and stakeholders to define data migration requirements and strategies.

Ensure data quality, data governance, and security standards are enforced throughout the ETL lifecycle.

Monitor and maintain data workflows to ensure performance, scalability, and fault tolerance.

Automate and orchestrate data workflows using scripting (Python, Bash) and cloud-native tools.

Support and troubleshoot production data pipelines and perform root cause analysis on failures.

Required Skills & Experience:

13+years of IT and 5+ years of experience in Data Engineering or ETL development.

3+ years of hands-on experience with AWS services, including:

o AWS Glue, AWS Lambda, AWS DMS, S3, Redshift, EMR, and Step Functions.

Proficiency in Red Hat Linux administration, shell scripting, and system troubleshooting.

Experience in designing and implementing ETL solutions for cloud migration projects.

Strong proficiency in Python, SQL, and cloud-native data processing frameworks.

Solid understanding of data warehousing, data lakes, and cloud-native architectures.

Familiarity with DevOps practices and tools such as CloudFormation, Terraform, or CI/CD pipelines is a plus.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.