{"schemaVersion":"jobsearcher.job.v1","id":"3e99beeb4dd7298ce992ce83","url":"https://jobsearcher.com/jobs/3e99beeb4dd7298ce992ce83","canonicalUrl":"https://jobsearcher.com/jobs/3e99beeb4dd7298ce992ce83","title":"DataOps Engineer","description":"DataOps Engineer Requirements:\nBachelor's degree in Computer Science, Computer Engineering, or a related technical degree; four years related experience; or equivalent combination of education and experience\n2+ years experience in data streaming technologies, such as Kafka\n2+ years experience using ETL (Extract, Transform, and Load) concepts\nExperience with querying and designing databases using one or more of the following: MySQL, MS SQL, Oracle SQL, or other professional database system\nAbility to work in teams and collaborate with others to clarify requirements, quickly identify problems, and collaboratively find creative solutions\nAbility to assist in documenting requirements as well as resolve conflicts or ambiguities\n\nNice to Have Skills:\n4 or more years experience in programming using one or more of the following: Java, C++, Perl, Python, or advanced Shell scripting.\n3 or more years of experience in implementing data-driven solutions using tools such as Hadoop, Impala, Hive, NiFi, Athena, Redshift, BigTable, or Airflow.\n2 or more years experience in machine learning and statistical modeling\nExperience in Cloud Native tools, such as Kubernetes and Docker\nExperience with using the R statistical computing language\nExperience with Agile at Scale, SAFe, and Lean Systems Engineering\nDataOps Engineer Responsibilities:\nDevelop high-volume, low-latency, data-driven solutions utilizing current and next generation technologies to meet evolving business needs\nAcquire big data input from numerous partners. Key technologies may include Python, Airflow, Prometheus, and Kafka.\nNormalize complicated data sources to convert potentially unusable data into a format that can be efficiently used by software and/or employees. Key technologies may include Spark, Kinesis, Lambda\nBuild a CI/CD pipeline for our data software to ensure we keep quality high and time to market low. Key technologies may include Gitlab.","company":"Cedent","rawCompany":"cedent","city":"Wyoming","state":"WV","isRemote":false,"isActive":false,"createdAt":"2026-08-15T12:42:00.174Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"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":"DataOps Engineer","description":"DataOps Engineer Requirements:\nBachelor's degree in Computer Science, Computer Engineering, or a related technical degree; four years related experience; or equivalent combination of education and experience\n2+ years experience in data streaming technologies, such as Kafka\n2+ years experience using ETL (Extract, Transform, and Load) concepts\nExperience with querying and designing databases using one or more of the following: MySQL, MS SQL, Oracle SQL, or other professional database system\nAbility to work in teams and collaborate with others to clarify requirements, quickly identify problems, and collaboratively find creative solutions\nAbility to assist in documenting requirements as well as resolve conflicts or ambiguities\n\nNice to Have Skills:\n4 or more years experience in programming using one or more of the following: Java, C++, Perl, Python, or advanced Shell scripting.\n3 or more years of experience in implementing data-driven solutions using tools such as Hadoop, Impala, Hive, NiFi, Athena, Redshift, BigTable, or Airflow.\n2 or more years experience in machine learning and statistical modeling\nExperience in Cloud Native tools, such as Kubernetes and Docker\nExperience with using the R statistical computing language\nExperience with Agile at Scale, SAFe, and Lean Systems Engineering\nDataOps Engineer Responsibilities:\nDevelop high-volume, low-latency, data-driven solutions utilizing current and next generation technologies to meet evolving business needs\nAcquire big data input from numerous partners. 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