{"schemaVersion":"jobsearcher.job.v1","id":"f0b59e18867c8e30ca050ad1","url":"https://jobsearcher.com/jobs/f0b59e18867c8e30ca050ad1","canonicalUrl":"https://jobsearcher.com/jobs/f0b59e18867c8e30ca050ad1","title":"AWS Data Engineer","description":"JD: Client is seeking an experienced AWS Data Engineer to design, build, and support scalable cloud-based data pipelines. The ideal candidate will have strong hands-on experience with Python, PySpark, ETL development, and AWS data services. This person will work with engineering, analytics, and business teams to process large datasets and deliver reliable, production-ready data solutions. Key Responsibilities * Design, develop, and maintain scalable ETL and data-processing pipelines. Build data-engineering solutions using Python and PySpark. Process and transform large structured and unstructured datasets. Develop cloud-based data solutions using AWS services. Monitor data pipelines and troubleshoot data-quality and performance issues. Optimize ETL workflows for reliability, scalability, and efficiency. Partner with application, analytics, and business teams to understand data requirements. Perform unit testing, code reviews, deployments, and production support. Follow data security, governance, and engineering best practices. Document technical designs, workflows, and operational procedures. Required Qualifications * Minimum 7 years of data engineering experience. Strong hands-on experience with Python, PySpark, ETL, and AWS. Strong SQL and data-transformation skills. Experience processing large datasets in distributed environments. Understanding of data modeling and cloud-based data-pipeline architecture. Experience troubleshooting and supporting production data pipelines. Strong communication and problem-solving skills. Preferred Qualifications * Hands-on Databricks experience. Experience with cloud-based data lakes and distributed data-processing platforms.","company":"Interon It Solutions","rawCompany":"interon it solutions","city":"Gaithersburg","state":"MD","isRemote":false,"isActive":false,"createdAt":"2026-08-27T09:01:54.593Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AWS Data Engineer","description":"JD: Client is seeking an experienced AWS Data Engineer to design, build, and support scalable cloud-based data pipelines. The ideal candidate will have strong hands-on experience with Python, PySpark, ETL development, and AWS data services. This person will work with engineering, analytics, and business teams to process large datasets and deliver reliable, production-ready data solutions. Key Responsibilities * Design, develop, and maintain scalable ETL and data-processing pipelines. Build data-engineering solutions using Python and PySpark. Process and transform large structured and unstructured datasets. Develop cloud-based data solutions using AWS services. Monitor data pipelines and troubleshoot data-quality and performance issues. Optimize ETL workflows for reliability, scalability, and efficiency. Partner with application, analytics, and business teams to understand data requirements. Perform unit testing, code reviews, deployments, and production support. Follow data security, governance, and engineering best practices. Document technical designs, workflows, and operational procedures. Required Qualifications * Minimum 7 years of data engineering experience. Strong hands-on experience with Python, PySpark, ETL, and AWS. Strong SQL and data-transformation skills. Experience processing large datasets in distributed environments. Understanding of data modeling and cloud-based data-pipeline architecture. Experience troubleshooting and supporting production data pipelines. Strong communication and problem-solving skills. Preferred Qualifications * Hands-on Databricks experience. Experience with cloud-based data lakes and distributed data-processing platforms.","datePosted":"2026-08-27T09:01:54.593Z","dateModified":"2026-08-27T09:01:54.593Z","hiringOrganization":{"@type":"Organization","name":"Interon It Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Gaithersburg","addressRegion":"MD","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"f0b59e18867c8e30ca050ad1"},"url":"https://jobsearcher.com/jobs/f0b59e18867c8e30ca050ad1"}}