AWS Data Engineer — Enterprise ETL & Big Data Pipelines

MACHINE LEARNING TECHNOLOGIES LLC; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Chicago, IL is seeking an AWS Data Engineer to design and optimize enterprise ETL pipelines. You will build scalable data workflows using AWS Glue, Python, PySpark, and SQL, while ensuring data quality and performance across S3, Redshift, Lambda, and related services.

The role requires 6+ years in ETL and SQL, 3–4 years with Python/PySpark and AWS Cloud services, plus hands-on DevOps and CI/CD experience.

Qualifications

• 6+ years of ETL development, data integration, transformation, and scheduling.
• 6+ years of strong SQL queries and optimization.
• 3-4 years of Python/PySpark with large-scale datasets.
• 3-4 years of AWS Cloud experience with Glue, S3, Redshift, Lambda, Step Functions, RDS Aurora/MySQL, CloudWatch, SNS, SQS, EventBridge.
• 3+ years of Big Data processing, data modeling, and scalable architectures.
• Hands-on DevOps experience with Harness, YAML, and AWS CloudFormation.
• Strong database troubleshooting, 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 performance

Tools

Harness

AWS CloudFormation

YAML

Dynatrace

Datadog

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Chicago, IL is seeking an AWS Data Engineer to design and optimize enterprise ETL pipelines. You will build scalable data workflows using AWS Glue, Python, PySpark, and SQL, while ensuring data quality and performance across S3, Redshift, Lambda, and related services.

The role requires 6+ years in ETL and SQL, 3–4 years with Python/PySpark and AWS Cloud services, plus hands-on DevOps and CI/CD experience.