{"schemaVersion":"jobsearcher.job.v1","id":"bc545b2f48b174729a33417b","url":"https://jobsearcher.com/jobs/bc545b2f48b174729a33417b","canonicalUrl":"https://jobsearcher.com/jobs/bc545b2f48b174729a33417b","title":"Store AI Agent - Onshore Data Engineer (Python, Pytorch, NodeJS)","description":"Dallas, TX, United States (On-site)\n Contract (9 months 5 days)\n Published 1 day ago\nDatabricks Platform\ncloud platforms\nDocker & Kubernetes\ndata modeling\nmlops\nDevOps & CI/CD\nPySpark/Python\n\nWe are seeking a highly skilled Data Engineer with strong expertise in Databricks, Python, and PyTorch to design, develop, and optimize scalable data and machine learning pipelines. The ideal candidate will be responsible for building cloud-native data platforms, enabling advanced analytics, and supporting AI/ML initiatives through robust data engineering practices.\n\nThis role requires hands-on experience in large-scale data processing, feature engineering, model deployment support, and performance optimization across modern data ecosystems.\n\nKey Responsibilities:\n\nData Engineering & Platform Development:\n\nDesign, develop, and maintain scalable data pipelines using Databricks, PySpark, and Python.\n\nBuild and optimize batch and real-time data ingestion frameworks from diverse data sources.\n\nDevelop ETL/ELT solutions to support enterprise data warehousing, analytics, and AI/ML workloads.\n\nImplement data quality checks, validation frameworks, monitoring, and observability solutions.\n\nOptimize Databricks jobs, notebooks, clusters, and workflows for performance and cost efficiency.\n\nDesign and maintain Delta Lake architectures, data models, and metadata management solutions.\n\nMachine Learning Data Enablement:\n\nCollaborate with Data Scientists and ML Engineers to prepare training datasets and feature stores.\n\nSupport development and deployment of deep learning solutions using PyTorch.\n\nDevelop scalable feature engineering pipelines and data transformation frameworks.\n\nEnable model training, experimentation, and inference infrastructure on Databricks.\n\nIntegrate ML workflows with MLOps pipelines and CI/CD processes.\n\nCloud & DevOps:\n\nImplement DataOps and MLOps best practices.\n\nAutomate deployments using CI/CD pipelines.\n\nWork with cloud-native services for storage, security, monitoring, and orchestration.\n\nSupport infrastructure-as-code and environment automation initiatives.\n\nCollaboration & Governance:\n\nPartner with business, analytics, and data science teams to understand requirements and translate them into technical solutions.\n\nEnsure compliance with data governance, privacy, and security standards.\n\nParticipate in architecture reviews and technology evaluations.\n\nRequired Skills:\n\nTechnical Skills:\n\nStrong experience with Databricks Platform\n\nExpertise in Python\n\nStrong hands-on experience with PySpark\n\nExperience with PyTorch for machine learning and deep learning workloads\n\nKnowledge of Delta Lake, Unity Catalog, and Databricks Workflows\n\nExperience with ETL/ELT pipeline development\n\nStrong SQL and data modeling skills\n\nExperience with distributed computing and big data architectures\n\nKnowledge of REST APIs and data integration patterns\n\nGit version control and CI/CD tools\n\nCloud Platforms:\n\nExperience with one or more:\n\nMicrosoft Azure (preferred)\n\nAWS\n\nGoogle Cloud Platform (GCP)\n\nData Technologies:\n\nSpark\n\nKafka/Event Streaming\n\nAzure Data Factory or equivalent integration tools\n\nData Lake architectures\n\nData Warehousing solutions\n\nFeature Stores\n\nPreferred Skills:\n\nExperience with GenAI and LLM data pipelines.\n\nKnowledge of MLflow and MLOps frameworks.\n\nHands-on experience with Docker and Kubernetes.\n\nExperience with real-time streaming architectures.\n\nFamiliarity with vector databases and AI platforms.\n\nCertifications in Databricks or Cloud platforms.\n\nQualifications:\n\nBachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.\n\n5+ years of experience in Data Engineering.\n\n3+ years of experience with Databricks and cloud-based data platforms.\n\nExperience supporting machine learning and AI use cases using PyTorch.\n\nNice-to-Have Experience:\n\nRetail, QSR, Restaurant Technology, Digital Commerce, or Customer Analytics domains.\n\nLarge-scale enterprise data modernization initiatives.\n\nAI/ML and advanced analytics implementations.\n\nThe pay range that the employer in good faith reasonably expects to pay for this position is $39.30/hour - $61.40/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.\n\nTundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.","company":"Capgemini","rawCompany":"capgemini","city":"Dallas","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-10-16T09:21:43.443Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"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":"Store AI Agent - Onshore Data Engineer (Python, Pytorch, NodeJS)","description":"Dallas, TX, United States (On-site)\n Contract (9 months 5 days)\n Published 1 day ago\nDatabricks Platform\ncloud platforms\nDocker & Kubernetes\ndata modeling\nmlops\nDevOps & CI/CD\nPySpark/Python\n\nWe are seeking a highly skilled Data Engineer with strong expertise in Databricks, Python, and PyTorch to design, develop, and optimize scalable data and machine learning pipelines. The ideal candidate will be responsible for building cloud-native data platforms, enabling advanced analytics, and supporting AI/ML initiatives through robust data engineering practices.\n\nThis role requires hands-on experience in large-scale data processing, feature engineering, model deployment support, and performance optimization across modern data ecosystems.\n\nKey Responsibilities:\n\nData Engineering & Platform Development:\n\nDesign, develop, and maintain scalable data pipelines using Databricks, PySpark, and Python.\n\nBuild and optimize batch and real-time data ingestion frameworks from diverse data sources.\n\nDevelop ETL/ELT solutions to support enterprise data warehousing, analytics, and AI/ML workloads.\n\nImplement data quality checks, validation frameworks, monitoring, and observability solutions.\n\nOptimize Databricks jobs, notebooks, clusters, and workflows for performance and cost efficiency.\n\nDesign and maintain Delta Lake architectures, data models, and metadata management solutions.\n\nMachine Learning Data Enablement:\n\nCollaborate with Data Scientists and ML Engineers to prepare training datasets and feature stores.\n\nSupport development and deployment of deep learning solutions using PyTorch.\n\nDevelop scalable feature engineering pipelines and data transformation frameworks.\n\nEnable model training, experimentation, and inference infrastructure on Databricks.\n\nIntegrate ML workflows with MLOps pipelines and CI/CD processes.\n\nCloud & DevOps:\n\nImplement DataOps and MLOps best practices.\n\nAutomate deployments using CI/CD pipelines.\n\nWork with cloud-native services for storage, security, monitoring, and orchestration.\n\nSupport infrastructure-as-code and environment automation initiatives.\n\nCollaboration & Governance:\n\nPartner with business, analytics, and data science teams to understand requirements and translate them into technical solutions.\n\nEnsure compliance with data governance, privacy, and security standards.\n\nParticipate in architecture reviews and technology evaluations.\n\nRequired Skills:\n\nTechnical Skills:\n\nStrong experience with Databricks Platform\n\nExpertise in Python\n\nStrong hands-on experience with PySpark\n\nExperience with PyTorch for machine learning and deep learning workloads\n\nKnowledge of Delta Lake, Unity Catalog, and Databricks Workflows\n\nExperience with ETL/ELT pipeline development\n\nStrong SQL and data modeling skills\n\nExperience with distributed computing and big data architectures\n\nKnowledge of REST APIs and data integration patterns\n\nGit version control and CI/CD tools\n\nCloud Platforms:\n\nExperience with one or more:\n\nMicrosoft Azure (preferred)\n\nAWS\n\nGoogle Cloud Platform (GCP)\n\nData Technologies:\n\nSpark\n\nKafka/Event Streaming\n\nAzure Data Factory or equivalent integration tools\n\nData Lake architectures\n\nData Warehousing solutions\n\nFeature Stores\n\nPreferred Skills:\n\nExperience with GenAI and LLM data pipelines.\n\nKnowledge of MLflow and MLOps frameworks.\n\nHands-on experience with Docker and Kubernetes.\n\nExperience with real-time streaming architectures.\n\nFamiliarity with vector databases and AI platforms.\n\nCertifications in Databricks or Cloud platforms.\n\nQualifications:\n\nBachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.\n\n5+ years of experience in Data Engineering.\n\n3+ years of experience with Databricks and cloud-based data platforms.\n\nExperience supporting machine learning and AI use cases using PyTorch.\n\nNice-to-Have Experience:\n\nRetail, QSR, Restaurant Technology, Digital Commerce, or Customer Analytics domains.\n\nLarge-scale enterprise data modernization initiatives.\n\nAI/ML and advanced analytics implementations.\n\nThe pay range that the employer in good faith reasonably expects to pay for this position is $39.30/hour - $61.40/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.\n\nTundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.","datePosted":"2026-10-16T09:21:43.443Z","dateModified":"2026-10-16T09:21:43.443Z","hiringOrganization":{"@type":"Organization","name":"Capgemini","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bc545b2f48b174729a33417b"},"url":"https://jobsearcher.com/jobs/bc545b2f48b174729a33417b"}}