STAFFXPERT LLC
AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Data Engineer with a contract length of "Unknown" and a pay rate of "Unknown." It is hybrid in Chicago, IL / Lafayette, LA / Nashville, TN / Richardson, TX. Key skills include Python, PySpark, AWS Glue, and SQL.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 20, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Chicago, IL
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🧠 - Skills detailed
#SQL Queries #Version Control #Data Engineering #SQS (Simple Queue Service) #Spark (Apache Spark) #GIT #Scala #Data Processing #Cloud #PostgreSQL #S3 (Amazon Simple Storage Service) #Code Reviews #Python #Compliance #SNS (Simple Notification Service) #SQL (Structured Query Language) #AWS (Amazon Web Services) #Automated Testing #Security #AWS Glue #Databases #Monitoring #Lambda (AWS Lambda) #Observability #Scrum #Data Pipeline #PySpark #DevOps #Documentation #Data Governance #"ETL (Extract #Transform #Load)" #Oracle #Agile
Role description
Location
Hybrid Chicago, IL / Lafayette, LA / Nashville, TN / Richardson, TX
Job Summary
STAFFXPERT LLC is seeking an AWS Data Engineer on behalf of our client in multiple U.S. locations. This role is responsible for designing, developing, and optimizing scalable cloud-based data pipelines and ETL solutions within an AWS ecosystem. The ideal candidate will bring strong expertise in PySpark, Python, AWS Glue, and relational databases, along with a passion for building high-performance, reliable, and secure data platforms.
Key Responsibilities
• Design, build, and maintain scalable ETL and data processing pipelines using Python, PySpark, and AWS Glue
• Develop cloud-native data solutions leveraging AWS services such as S3, Lambda, Step Functions, ECS, SNS, and SQS
• Optimize Spark jobs, SQL queries, and data workflows for performance and scalability
• Develop and maintain PL/SQL scripts and database solutions in Oracle, PostgreSQL, or similar relational databases
• Implement software engineering best practices including version control, automated testing, CI/CD, and code reviews
• Monitor production data environments, troubleshoot issues, and perform root cause analysis
• Collaborate with cross-functional teams including architects, developers, analysts, and business stakeholders
• Maintain technical documentation and support operational excellence initiatives
Required Qualifications
• Strong hands-on experience building production-grade data pipelines using Python and PySpark
• Expertise with AWS cloud services including S3, Glue, Lambda, Step Functions, ECS, SNS, and SQS
• Strong SQL and PL/SQL development experience with relational databases such as Oracle or PostgreSQL
• Experience with Spark performance tuning and large-scale data processing
• Solid understanding of software development best practices including Git, testing, and CI/CD pipelines
• Experience with monitoring, observability, alerting, and production support processes
• Strong analytical, troubleshooting, and problem-solving skills
• Excellent verbal and written communication skills
Preferred Qualifications
• Experience working with enterprise-scale cloud data platforms
• Familiarity with DevOps practices and Infrastructure-as-Code tools
• Knowledge of data governance, security, and compliance standards
• Experience working in Agile/Scrum environments
Location
Hybrid Chicago, IL / Lafayette, LA / Nashville, TN / Richardson, TX
Job Summary
STAFFXPERT LLC is seeking an AWS Data Engineer on behalf of our client in multiple U.S. locations. This role is responsible for designing, developing, and optimizing scalable cloud-based data pipelines and ETL solutions within an AWS ecosystem. The ideal candidate will bring strong expertise in PySpark, Python, AWS Glue, and relational databases, along with a passion for building high-performance, reliable, and secure data platforms.
Key Responsibilities
• Design, build, and maintain scalable ETL and data processing pipelines using Python, PySpark, and AWS Glue
• Develop cloud-native data solutions leveraging AWS services such as S3, Lambda, Step Functions, ECS, SNS, and SQS
• Optimize Spark jobs, SQL queries, and data workflows for performance and scalability
• Develop and maintain PL/SQL scripts and database solutions in Oracle, PostgreSQL, or similar relational databases
• Implement software engineering best practices including version control, automated testing, CI/CD, and code reviews
• Monitor production data environments, troubleshoot issues, and perform root cause analysis
• Collaborate with cross-functional teams including architects, developers, analysts, and business stakeholders
• Maintain technical documentation and support operational excellence initiatives
Required Qualifications
• Strong hands-on experience building production-grade data pipelines using Python and PySpark
• Expertise with AWS cloud services including S3, Glue, Lambda, Step Functions, ECS, SNS, and SQS
• Strong SQL and PL/SQL development experience with relational databases such as Oracle or PostgreSQL
• Experience with Spark performance tuning and large-scale data processing
• Solid understanding of software development best practices including Git, testing, and CI/CD pipelines
• Experience with monitoring, observability, alerting, and production support processes
• Strong analytical, troubleshooting, and problem-solving skills
• Excellent verbal and written communication skills
Preferred Qualifications
• Experience working with enterprise-scale cloud data platforms
• Familiarity with DevOps practices and Infrastructure-as-Code tools
• Knowledge of data governance, security, and compliance standards
• Experience working in Agile/Scrum environments
