Senior AWS Data Engineer – ETL & Big Data

Machine Learning Technologies, LLC; Chicago (IL); On-site; USD 110,000 - 140,000; Full time

Job summary

Machine Learning Technologies, LLC in Chicago seeks a Senior ETL Developer to design, build, and optimize enterprise-scale data pipelines in AWS. You will leverage Python, PySpark, and SQL to develop scalable data processing solutions and integrate AWS services such as S3, Redshift, Lambda, and Step Functions.

The role requires 6+ years of ETL experience, 3–4 years of Python/PySpark and AWS Cloud experience, and hands-on skills in DevOps with Harness, YAML, and CloudFormation.

Qualifications

• ETL development experience of 6+ years.
• SQL: 6+ years of strong experience writing and optimizing complex SQL queries.
• Python / PySpark: 3–4 years of hands-on programming with large-scale datasets.
• AWS Cloud: 3–4 years of experience with AWS Glue, S3, Redshift, Lambda, Step Functions, RDS Aurora/MySQL, CloudWatch, SNS, SQS, and EventBridge.
• Big Data: 3+ years of experience in Big Data processing, data modeling, and scalable data architectures.
• DevOps / CI/CD: Harness, YAML, and AWS CloudFormation.
• Database Troubleshooting: Strong understanding of RDS MySQL, database performance tuning, and production support.

Responsibilities

• Design, develop, implement, and optimize enterprise-scale ETL pipelines and backend data processing solutions.
• Build and maintain scalable data pipelines using AWS Glue, Python, PySpark, and SQL.
• Develop complex SQL queries, stored procedures, and data transformation workflows.
• Work with AWS services including S3, Redshift, Lambda, Step Functions, RDS, CloudWatch, SNS, SQS, and EventBridge.
• Perform data cleansing, profiling, transformation, and workflow scheduling.
• Troubleshoot ETL failures, database performance issues, and production incidents.
• Implement CI/CD pipelines and Infrastructure as Code using Harness, YAML, and AWS CloudFormation.
• Collaborate with architects, developers, and business stakeholders to deliver enterprise data solutions.
• Perform root cause analysis and provide production support for critical ETL processes.
• Maintain coding standards, technical documentation, and ETL development best practices.

Skills

ETL Development

SQL

Python / PySpark

AWS Cloud

Big Data

DevOps / CI/CD

Database Troubleshooting

Team Leadership

Apache Iceberg

Datadog

Tools

Apache Iceberg

Dynatrace

Datadog

Job description

Machine Learning Technologies, LLC in Chicago seeks a Senior ETL Developer to design, build, and optimize enterprise-scale data pipelines in AWS. You will leverage Python, PySpark, and SQL to develop scalable data processing solutions and integrate AWS services such as S3, Redshift, Lambda, and Step Functions.

The role requires 6+ years of ETL experience, 3–4 years of Python/PySpark and AWS Cloud experience, and hands-on skills in DevOps with Harness, YAML, and CloudFormation.