{"schemaVersion":"jobsearcher.job.v1","id":"58dae066f88e170f936e0160","url":"https://jobsearcher.com/jobs/58dae066f88e170f936e0160","canonicalUrl":"https://jobsearcher.com/jobs/58dae066f88e170f936e0160","title":"Data Engineering Intern","description":"TDK SensEI is transforming how sensor data is collected, processed, and leveraged powering intelligent, data-driven decision-making across industrial environments. As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a global leader in sensor technology, SensEI operates at the forefront of industrial AI and analytics.\r\nThe Data Engineering Intern supports the development of scalable data systems and infrastructure that power our machine learning–based equipment monitoring platform. In this role, the intern will work with large-scale sensor datasets, cloud-based technologies, and modern data pipelines, while collaborating closely with software and machine learning engineers to enable advanced analytics and AI applications.\r\nThis internship provides hands-on experience in building production-ready data systems within a fast-paced, innovative environment.\r\nKey Responsibilities\r\nBuild, maintain, and optimize ETL/ELT pipelines for processing sensor and operational data\r\nDevelop data workflows and automation using Python, SQL, and AWS services\r\nSupport data ingestion, transformation, validation, and monitoring processes\r\nWork with structured and semi-structured data from cloud and edge-based systems\r\nCollaborate with software and ML engineers to prepare datasets for analytics and machine learning models\r\nAssist with integration and optimization of OLTP and OLAP systems\r\nTroubleshoot pipeline issues and contribute to improvements in data reliability and performance\r\nAdditional Responsibilities\r\nCreate and maintain documentation, including data flows, system diagrams, and technical specifications\r\nParticipate in code reviews and adhere to engineering best practices\r\nSupport initiatives to improve data quality, observability, and operational efficiency\r\nContribute to continuous improvement of data infrastructure and workflows\r\nOther Duties\r\nPerform other related duties and ad hoc projects as assigned to support departmental and organizational goals\r\nMaintain awareness of and follow all workplace safety guidelines and promote a culture of well-being\r\nEnsure work is performed in accordance with established quality control and assurance processes\r\nAdhere to the company's values and code of conduct and uphold the highest standards of honesty, integrity, and ethical behavior in all business activities\r\nQualifications\r\nEducation / Experience\r\nCurrently pursuing a Bachelor's or Master's degree in a related technical field\r\nHands-on experience with Python and SQL\r\nExposure to data pipelines, ETL/ELT processes, or data warehousing concepts\r\nFamiliarity with relational and/or analytical databases (e.g., PostgreSQL, MySQL, Redshift)\r\nExposure to cloud platforms, preferably AWS\r\nKnowledge, Skills, and Abilities\r\nStrong foundation in Python programming and SQL/database fundamentals\r\nBasic understanding of data engineering concepts, including pipelines, transformation, and storage\r\nFamiliarity with cloud computing and distributed systems\r\nAnalytical mindset with strong problem-solving capabilities\r\nAbility to quickly learn new tools, technologies, and frameworks\r\nStrong attention to detail and commitment to data accuracy and quality\r\nEffective communication skills, both written and verbal\r\nAbility to collaborate in cross-functional team environments\r\nPreferred / Bonus Qualifications\r\nExperience with workflow orchestration tools (e.g., Apache Airflow)\r\nFamiliarity with AWS services such as S3, Lambda, Glue, or Redshift\r\nExposure to Docker, Linux, or shell scripting\r\nUnderstanding of OLTP vs. OLAP systems\r\nExperience with data lakes, data warehousing, or analytics platforms\r\nInterest in machine learning and data-driven systems\r\nExperience with Git or version control systems\r\nJ-18808-Ljbffr","company":"Valid8 Financial","rawCompany":"valid8 financial","city":"San Clemente","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-06-22T01:16:31.331Z","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":"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":"Data Engineering Intern","description":"TDK SensEI is transforming how sensor data is collected, processed, and leveraged powering intelligent, data-driven decision-making across industrial environments. As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a global leader in sensor technology, SensEI operates at the forefront of industrial AI and analytics.\r\nThe Data Engineering Intern supports the development of scalable data systems and infrastructure that power our machine learning–based equipment monitoring platform. In this role, the intern will work with large-scale sensor datasets, cloud-based technologies, and modern data pipelines, while collaborating closely with software and machine learning engineers to enable advanced analytics and AI applications.\r\nThis internship provides hands-on experience in building production-ready data systems within a fast-paced, innovative environment.\r\nKey Responsibilities\r\nBuild, maintain, and optimize ETL/ELT pipelines for processing sensor and operational data\r\nDevelop data workflows and automation using Python, SQL, and AWS services\r\nSupport data ingestion, transformation, validation, and monitoring processes\r\nWork with structured and semi-structured data from cloud and edge-based systems\r\nCollaborate with software and ML engineers to prepare datasets for analytics and machine learning models\r\nAssist with integration and optimization of OLTP and OLAP systems\r\nTroubleshoot pipeline issues and contribute to improvements in data reliability and performance\r\nAdditional Responsibilities\r\nCreate and maintain documentation, including data flows, system diagrams, and technical specifications\r\nParticipate in code reviews and adhere to engineering best practices\r\nSupport initiatives to improve data quality, observability, and operational efficiency\r\nContribute to continuous improvement of data infrastructure and workflows\r\nOther Duties\r\nPerform other related duties and ad hoc projects as assigned to support departmental and organizational goals\r\nMaintain awareness of and follow all workplace safety guidelines and promote a culture of well-being\r\nEnsure work is performed in accordance with established quality control and assurance processes\r\nAdhere to the company's values and code of conduct and uphold the highest standards of honesty, integrity, and ethical behavior in all business activities\r\nQualifications\r\nEducation / Experience\r\nCurrently pursuing a Bachelor's or Master's degree in a related technical field\r\nHands-on experience with Python and SQL\r\nExposure to data pipelines, ETL/ELT processes, or data warehousing concepts\r\nFamiliarity with relational and/or analytical databases (e.g., PostgreSQL, MySQL, Redshift)\r\nExposure to cloud platforms, preferably AWS\r\nKnowledge, Skills, and Abilities\r\nStrong foundation in Python programming and SQL/database fundamentals\r\nBasic understanding of data engineering concepts, including pipelines, transformation, and storage\r\nFamiliarity with cloud computing and distributed systems\r\nAnalytical mindset with strong problem-solving capabilities\r\nAbility to quickly learn new tools, technologies, and frameworks\r\nStrong attention to detail and commitment to data accuracy and quality\r\nEffective communication skills, both written and verbal\r\nAbility to collaborate in cross-functional team environments\r\nPreferred / Bonus Qualifications\r\nExperience with workflow orchestration tools (e.g., Apache Airflow)\r\nFamiliarity with AWS services such as S3, Lambda, Glue, or Redshift\r\nExposure to Docker, Linux, or shell scripting\r\nUnderstanding of OLTP vs. OLAP systems\r\nExperience with data lakes, data warehousing, or analytics platforms\r\nInterest in machine learning and data-driven systems\r\nExperience with Git or version control systems\r\nJ-18808-Ljbffr","datePosted":"2026-06-22T01:16:31.331Z","dateModified":"2026-06-22T01:16:31.331Z","hiringOrganization":{"@type":"Organization","name":"Valid8 Financial","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Clemente","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"58dae066f88e170f936e0160"},"url":"https://jobsearcher.com/jobs/58dae066f88e170f936e0160"}}