{"schemaVersion":"jobsearcher.job.v1","id":"1a3af039ebea5e9fa51982f6","url":"https://jobsearcher.com/jobs/1a3af039ebea5e9fa51982f6","canonicalUrl":"https://jobsearcher.com/jobs/1a3af039ebea5e9fa51982f6","title":"Senior Data Engineer (Python / AWS / ML Pipelines)","description":"This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Python / AWS / ML Pipelines) based in Germany.\r\nAs a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines in a production environment.\r\nYou will work across data engineering, cloud infrastructure, and machine learning operations to turn models into reliable production workflows.\r\nThe role focuses heavily on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure.\r\nYou will collaborate closely with Data Scientists and ML Engineers to productionize forecasting and data-driven solutions.\r\nYou will also help improve the reliability, performance, and observability of critical data pipelines.\r\nWorking within distributed Agile teams, you will contribute to architecture decisions and technical improvements across the data platform.\r\nThis is an opportunity to work on challenging production systems while continuing to develop your cloud and ML engineering expertise.\r\nAccountabilitiesBuild, maintain, and improve production-grade data and machine learning pipelines supporting forecasting and data-driven decision-making.\r\nDevelop ETL and data-processing workflows using Python, ensuring they are scalable, reliable, and maintainable.\r\nDesign and orchestrate workflows using technologies such as Apache Airflow and AWS Step Functions.\r\nUse AWS Glue for data processing, transformation, and pipeline execution.\r\nSupport the deployment and operationalization of machine learning models using AWS SageMaker.\r\nWork closely with Data Scientists and ML Engineers to move models and analytical solutions reliably into production.\r\nMonitor pipeline health and performance, troubleshoot production issues, and implement improvements to reliability, scalability, and efficiency.\r\nContribute to architectural and technical decisions related to the data platform, ML infrastructure, and production workflows.\r\nCollaborate effectively with distributed, cross-functional Agile teams and contribute ideas that improve engineering practices and delivery.\r\nRequirements:Strong professional experience with Python and its application to data engineering and production systems.\r\nProven experience building and maintaining data pipelines and/or machine learning pipelines in production.\r\nHands-on experience with Apache Airflow for workflow orchestration.\r\nPractical experience with AWS Step Functions and AWS Glue.\r\nExperience deploying and supporting machine learning models using AWS SageMaker.\r\nStrong hands-on experience with AWS cloud services and cloud-based production environments.\r\nExperience working with systems operating at significant scale, with a strong understanding of reliability and performance considerations.\r\nExperience collaborating closely with Data Scientists, ML Engineers, and other technical stakeholders.\r\nStrong troubleshooting, analytical, and problem-solving abilities.\r\nExcellent written and verbal English communication skills.\r\nComfortable working independently and collaboratively within distributed, cross-functional teams.\r\nExperience with GCP is a plus but not required.\r\nFamiliarity with monitoring and observability tools is also advantageous.\r\nBenefits:Collegial working environment where responsibility and decision-making are shared across the team.\r\nAgile culture where employees are encouraged to contribute ideas and influence technical direction.\r\nSupportive approach to learning from mistakes and continuously improving ways of working.\r\nOpportunities to work on different projects and broaden your technical experience.\r\nOngoing training, mentoring, and professional development.\r\nOpportunities for career growth and exposure to new technologies and challenges.\r\nPossibility of business travel.\r\nFlexible working arrangements appropriate to a distributed team.\r\nAdditional salary, healthcare, and other employment benefits may vary according to local terms in Slovenia.#J-18808-Ljbffr","company":"Lever","rawCompany":"lever","city":"New Bremen","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-10-04T01:34:19.258Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"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":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Data Engineer (Python / AWS / ML Pipelines)","description":"This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (Python / AWS / ML Pipelines) based in Germany.\r\nAs a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines in a production environment.\r\nYou will work across data engineering, cloud infrastructure, and machine learning operations to turn models into reliable production workflows.\r\nThe role focuses heavily on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure.\r\nYou will collaborate closely with Data Scientists and ML Engineers to productionize forecasting and data-driven solutions.\r\nYou will also help improve the reliability, performance, and observability of critical data pipelines.\r\nWorking within distributed Agile teams, you will contribute to architecture decisions and technical improvements across the data platform.\r\nThis is an opportunity to work on challenging production systems while continuing to develop your cloud and ML engineering expertise.\r\nAccountabilitiesBuild, maintain, and improve production-grade data and machine learning pipelines supporting forecasting and data-driven decision-making.\r\nDevelop ETL and data-processing workflows using Python, ensuring they are scalable, reliable, and maintainable.\r\nDesign and orchestrate workflows using technologies such as Apache Airflow and AWS Step Functions.\r\nUse AWS Glue for data processing, transformation, and pipeline execution.\r\nSupport the deployment and operationalization of machine learning models using AWS SageMaker.\r\nWork closely with Data Scientists and ML Engineers to move models and analytical solutions reliably into production.\r\nMonitor pipeline health and performance, troubleshoot production issues, and implement improvements to reliability, scalability, and efficiency.\r\nContribute to architectural and technical decisions related to the data platform, ML infrastructure, and production workflows.\r\nCollaborate effectively with distributed, cross-functional Agile teams and contribute ideas that improve engineering practices and delivery.\r\nRequirements:Strong professional experience with Python and its application to data engineering and production systems.\r\nProven experience building and maintaining data pipelines and/or machine learning pipelines in production.\r\nHands-on experience with Apache Airflow for workflow orchestration.\r\nPractical experience with AWS Step Functions and AWS Glue.\r\nExperience deploying and supporting machine learning models using AWS SageMaker.\r\nStrong hands-on experience with AWS cloud services and cloud-based production environments.\r\nExperience working with systems operating at significant scale, with a strong understanding of reliability and performance considerations.\r\nExperience collaborating closely with Data Scientists, ML Engineers, and other technical stakeholders.\r\nStrong troubleshooting, analytical, and problem-solving abilities.\r\nExcellent written and verbal English communication skills.\r\nComfortable working independently and collaboratively within distributed, cross-functional teams.\r\nExperience with GCP is a plus but not required.\r\nFamiliarity with monitoring and observability tools is also advantageous.\r\nBenefits:Collegial working environment where responsibility and decision-making are shared across the team.\r\nAgile culture where employees are encouraged to contribute ideas and influence technical direction.\r\nSupportive approach to learning from mistakes and continuously improving ways of working.\r\nOpportunities to work on different projects and broaden your technical experience.\r\nOngoing training, mentoring, and professional development.\r\nOpportunities for career growth and exposure to new technologies and challenges.\r\nPossibility of business travel.\r\nFlexible working arrangements appropriate to a distributed team.\r\nAdditional salary, healthcare, and other employment benefits may vary according to local terms in Slovenia.#J-18808-Ljbffr","datePosted":"2026-10-04T01:34:19.258Z","dateModified":"2026-10-04T01:34:19.258Z","hiringOrganization":{"@type":"Organization","name":"Lever","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New Bremen","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1a3af039ebea5e9fa51982f6"},"url":"https://jobsearcher.com/jobs/1a3af039ebea5e9fa51982f6"}}