AWS Data Engineering

Machine Learning Technologies, LLC; Chicago (IL); Vor Ort; USD 110.000 - 140.000; Vollzeit

Zusammenfassung

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.

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

ETL Development

SQL

Python / PySpark

AWS Cloud

Big Data

DevOps / CI/CD

Database Troubleshooting

Team Leadership

Apache Iceberg

Datadog

Tools

Apache Iceberg

Dynatrace

Datadog

Jobbeschreibung

We are seeking an experienced Senior ETL Developer with strong hands-on expertise in AWS cloud services, Python, PySpark, SQL, and large-scale enterprise data processing.

The ideal candidate will be responsible for designing, developing, optimizing, and maintaining scalable ETL pipelines and data analytics solutions within the AWS ecosystem.

Key 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.

Mandatory Technical Skills:

ETL Development: 6+ years of experience in ETL development, data integration, transformation, and scheduling.

SQL: 6+ years of strong experience writing and optimizing complex SQL queries.

Python / PySpark: 3–4 years of hands-on programming experience 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: Hands-on experience with Harness, YAML, and AWS CloudFormation.

Database Troubleshooting: Strong understanding of RDS MySQL, database performance tuning, and production support.

Preferred Skills:

Experience leading ETL or Data Engineering teams.

Hands-on experience with Apache Iceberg.

Experience with Dynatrace or Datadog.

Strong analytical, troubleshooting, and communication skills.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.