{"schemaVersion":"jobsearcher.job.v1","id":"b56ce84f90b7f76d5b30fd3e","url":"https://jobsearcher.com/jobs/b56ce84f90b7f76d5b30fd3e","canonicalUrl":"https://jobsearcher.com/jobs/b56ce84f90b7f76d5b30fd3e","title":"Data Engineer – Python, SQL, Spark, ETL | Dallas, TX (Onsite)","description":"Job Title: Data EngineerLocation: Dallas, TX (Onsite, 5 Days a Week)Duration: Long-TermJob Type: Contract / Long-Term EngagementJob SummaryWe are seeking experienced Data Engineers to join our team in Dallas, TX. This role focuses on designing, developing, enhancing, and maintaining enterprise data warehouses, data pipelines, and advanced analytics platforms. The ideal candidates will have strong programming and SQL skills, hands-on experience with ETL processes and big data technologies, and an understanding of scalable, secure data architectures.Candidates will collaborate with data scientists, analysts, and engineering teams to support advanced analytics initiatives, including machine learning, predictive modeling, and artificial intelligence.Number of Openings: 7Work Arrangement: 100% Onsite – Dallas, TX (5 days per week)Key ResponsibilitiesDesign, develop, enhance, and maintain enterprise data warehouses and advanced analytical applications.Apply data engineering principles, techniques, and best practices to build reliable and scalable data solutions.Maintain and optimize corporate data warehouses, analytical platforms, and data processing systems.Develop, debug, test, and optimize ETL processes and data pipelines to improve performance, scalability, and reliability.Design and implement data architectures that meet performance, scalability, security, and compliance requirements.Support advanced analytics initiatives involving machine learning, predictive modeling, and artificial intelligence.Collaborate with data scientists, data analysts, and cross-functional engineering teams to deliver analytics solutions.Implement data security measures, including encryption, access controls, and data protection mechanisms.Support data migration, data integration, and data transformation projects.Troubleshoot data processing issues and ensure data quality, consistency, and availability.Required QualificationsStrong understanding of data engineering principles, methodologies, and best practices.Proficiency in Python, Java, Scala, and SQL.Experience with big data technologies and platforms such as Apache Spark, Hadoop, or cloud-based data services.Knowledge of relational databases, database design, data modeling, and data warehouse concepts.Understanding of ETL/ELT processes, data integration, and data transformation techniques.Experience developing, maintaining, and troubleshooting data pipelines.Understanding of scalable data architecture, data security, and access control principles.Strong analytical, problem-solving, and debugging skills.Ability to collaborate effectively with data engineering, analytics, and data science teams.Willingness to work onsite in Dallas, TX, five days per week.Preferred QualificationsExperience supporting machine learning, predictive analytics, or AI-related data initiatives.Familiarity with cloud data platforms and modern data warehouse technologies.Experience with large-scale data processing, performance tuning, and data pipeline optimization.Knowledge of data governance, data quality, encryption, and regulatory compliance practices.Work Location and EngagementLocation: Dallas, TexasWork Arrangement: Fully onsite, Monday through FridayDuration: Long-term engagementOpen Positions: 7How to ApplyQualified candidates with experience in data engineering, SQL, Python, big data technologies, data warehousing, and ETL development are encouraged to apply. Candidates should be comfortable working onsite in Dallas, TX, five days a week.","company":"Qentelli","rawCompany":"qentelli","city":"Dallas","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-10-14T01:44:03.586Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-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"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer – Python, SQL, Spark, ETL | Dallas, TX (Onsite)","description":"Job Title: Data EngineerLocation: Dallas, TX (Onsite, 5 Days a Week)Duration: Long-TermJob Type: Contract / Long-Term EngagementJob SummaryWe are seeking experienced Data Engineers to join our team in Dallas, TX. This role focuses on designing, developing, enhancing, and maintaining enterprise data warehouses, data pipelines, and advanced analytics platforms. The ideal candidates will have strong programming and SQL skills, hands-on experience with ETL processes and big data technologies, and an understanding of scalable, secure data architectures.Candidates will collaborate with data scientists, analysts, and engineering teams to support advanced analytics initiatives, including machine learning, predictive modeling, and artificial intelligence.Number of Openings: 7Work Arrangement: 100% Onsite – Dallas, TX (5 days per week)Key ResponsibilitiesDesign, develop, enhance, and maintain enterprise data warehouses and advanced analytical applications.Apply data engineering principles, techniques, and best practices to build reliable and scalable data solutions.Maintain and optimize corporate data warehouses, analytical platforms, and data processing systems.Develop, debug, test, and optimize ETL processes and data pipelines to improve performance, scalability, and reliability.Design and implement data architectures that meet performance, scalability, security, and compliance requirements.Support advanced analytics initiatives involving machine learning, predictive modeling, and artificial intelligence.Collaborate with data scientists, data analysts, and cross-functional engineering teams to deliver analytics solutions.Implement data security measures, including encryption, access controls, and data protection mechanisms.Support data migration, data integration, and data transformation projects.Troubleshoot data processing issues and ensure data quality, consistency, and availability.Required QualificationsStrong understanding of data engineering principles, methodologies, and best practices.Proficiency in Python, Java, Scala, and SQL.Experience with big data technologies and platforms such as Apache Spark, Hadoop, or cloud-based data services.Knowledge of relational databases, database design, data modeling, and data warehouse concepts.Understanding of ETL/ELT processes, data integration, and data transformation techniques.Experience developing, maintaining, and troubleshooting data pipelines.Understanding of scalable data architecture, data security, and access control principles.Strong analytical, problem-solving, and debugging skills.Ability to collaborate effectively with data engineering, analytics, and data science teams.Willingness to work onsite in Dallas, TX, five days per week.Preferred QualificationsExperience supporting machine learning, predictive analytics, or AI-related data initiatives.Familiarity with cloud data platforms and modern data warehouse technologies.Experience with large-scale data processing, performance tuning, and data pipeline optimization.Knowledge of data governance, data quality, encryption, and regulatory compliance practices.Work Location and EngagementLocation: Dallas, TexasWork Arrangement: Fully onsite, Monday through FridayDuration: Long-term engagementOpen Positions: 7How to ApplyQualified candidates with experience in data engineering, SQL, Python, big data technologies, data warehousing, and ETL development are encouraged to apply. Candidates should be comfortable working onsite in Dallas, TX, five days a week.","datePosted":"2026-10-14T01:44:03.586Z","dateModified":"2026-10-14T01:44:03.586Z","hiringOrganization":{"@type":"Organization","name":"Qentelli","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b56ce84f90b7f76d5b30fd3e"},"url":"https://jobsearcher.com/jobs/b56ce84f90b7f76d5b30fd3e"}}