{"schemaVersion":"jobsearcher.job.v1","id":"b508756f859dcebcc080d1bc","url":"https://jobsearcher.com/jobs/b508756f859dcebcc080d1bc","canonicalUrl":"https://jobsearcher.com/jobs/b508756f859dcebcc080d1bc","title":"Data Engineer Level 2","description":"The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure, with strong hands-on skills in Databricks, Spark, Python, and cloud-based DataOps practices.\r\nThe Data Engineer will analyze, design, and develop data products, pipelines, and information architecture deliverables, focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform, GitHub, and GitHub Actions to deliver scalable, reliable, and secure data solutions.\r\nWork Location must be local. Interviews will be in person, onsite. Not only do they need to be local, but they also need to be willing to come on-site for their interview, as well as that they will be expected to work on-site with the team.\r\nResponsibilities\r\nAnalyze, design, and develop enterprise data solutions with a focus on Azure, Databricks, Spark, Python, and SQL\r\nDevelop, optimize, and maintain Spark/PySpark data pipelines, including managing performance issues such as data skew, partitioning, caching, and shuffle optimization\r\nBuild and support Delta Lake tables and data models for analytical and operational use cases\r\nApply reusable design patterns, data standards, and architecture guidelines across the enterprise, including collaboration with 84.51° when needed\r\nUse Terraform to provision and manage cloud and Databricks resources, supporting Infrastructure as Code (IaC) practices\r\nImplement and maintain CI/CD workflows using GitHub and GitHub Actions for source control, testing, and pipeline deployment\r\nManage Git-based workflows for Databricks notebooks, jobs, and data engineering artifacts\r\nTroubleshoot failures and improve reliability across Databricks jobs, clusters, and data pipelines\r\nApply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments\r\nWork closely with engineering teams to enhance tools, systems, development processes, and data security\r\nParticipate in the development and communication of data strategy, standards, and roadmaps\r\nDraft architectural diagrams, interface specifications, and other design documents\r\nPromote the reuse of data assets and contribute to enterprise data catalog practices\r\nDeliver timely and effective support and communication to stakeholders and end users\r\nMentor team members on data engineering principles, best practices, and emerging technologies\r\nQualifications\r\n5+ years of experience as a Data Engineer\r\nHands-on experience with Azure Databricks, Spark, and Python\r\nExperience with Delta Live Tables (DLT) or Databricks SQL\r\nStrong SQL and database background\r\nExperience with Azure Functions, messaging services, or orchestration tools\r\nFamiliarity with data governance, lineage, or cataloging tools (e.g., Purview, Unity Catalog)\r\nExperience monitoring and optimizing Databricks clusters or workflows\r\nExperience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms\r\nExperience with Terraform for cloud infrastructure provisioning\r\nExperience with GitHub and GitHub Actions for version control and CI/CD automation\r\nStrong understanding of distributed computing concepts (partitions, joins, shuffles, cluster behavior)\r\nFamiliarity with SDLC and modern engineering practices\r\nAbility to balance multiple priorities, work independently, and stay organized\r\nRequired Skills\r\nAzure Data Bricks\r\nPython\r\nSpark\r\nPreferred Skills\r\nProblem solving\r\nAttention to detail\r\nAbility to work independently and as part of an agile team","company":"Ascendum Kps","rawCompany":"ascendum kps","city":"Dayton","state":"OH","isRemote":false,"isActive":false,"createdAt":"2026-05-03T03:51:59.218Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"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":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer Level 2","description":"The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure, with strong hands-on skills in Databricks, Spark, Python, and cloud-based DataOps practices.\r\nThe Data Engineer will analyze, design, and develop data products, pipelines, and information architecture deliverables, focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI/CD using Terraform, GitHub, and GitHub Actions to deliver scalable, reliable, and secure data solutions.\r\nWork Location must be local. Interviews will be in person, onsite. Not only do they need to be local, but they also need to be willing to come on-site for their interview, as well as that they will be expected to work on-site with the team.\r\nResponsibilities\r\nAnalyze, design, and develop enterprise data solutions with a focus on Azure, Databricks, Spark, Python, and SQL\r\nDevelop, optimize, and maintain Spark/PySpark data pipelines, including managing performance issues such as data skew, partitioning, caching, and shuffle optimization\r\nBuild and support Delta Lake tables and data models for analytical and operational use cases\r\nApply reusable design patterns, data standards, and architecture guidelines across the enterprise, including collaboration with 84.51° when needed\r\nUse Terraform to provision and manage cloud and Databricks resources, supporting Infrastructure as Code (IaC) practices\r\nImplement and maintain CI/CD workflows using GitHub and GitHub Actions for source control, testing, and pipeline deployment\r\nManage Git-based workflows for Databricks notebooks, jobs, and data engineering artifacts\r\nTroubleshoot failures and improve reliability across Databricks jobs, clusters, and data pipelines\r\nApply cloud computing skills to deploy fixes, upgrades, and enhancements in Azure environments\r\nWork closely with engineering teams to enhance tools, systems, development processes, and data security\r\nParticipate in the development and communication of data strategy, standards, and roadmaps\r\nDraft architectural diagrams, interface specifications, and other design documents\r\nPromote the reuse of data assets and contribute to enterprise data catalog practices\r\nDeliver timely and effective support and communication to stakeholders and end users\r\nMentor team members on data engineering principles, best practices, and emerging technologies\r\nQualifications\r\n5+ years of experience as a Data Engineer\r\nHands-on experience with Azure Databricks, Spark, and Python\r\nExperience with Delta Live Tables (DLT) or Databricks SQL\r\nStrong SQL and database background\r\nExperience with Azure Functions, messaging services, or orchestration tools\r\nFamiliarity with data governance, lineage, or cataloging tools (e.g., Purview, Unity Catalog)\r\nExperience monitoring and optimizing Databricks clusters or workflows\r\nExperience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms\r\nExperience with Terraform for cloud infrastructure provisioning\r\nExperience with GitHub and GitHub Actions for version control and CI/CD automation\r\nStrong understanding of distributed computing concepts (partitions, joins, shuffles, cluster behavior)\r\nFamiliarity with SDLC and modern engineering practices\r\nAbility to balance multiple priorities, work independently, and stay organized\r\nRequired Skills\r\nAzure Data Bricks\r\nPython\r\nSpark\r\nPreferred Skills\r\nProblem solving\r\nAttention to detail\r\nAbility to work independently and as part of an agile team","datePosted":"2026-05-03T03:51:59.218Z","dateModified":"2026-05-03T03:51:59.218Z","hiringOrganization":{"@type":"Organization","name":"Ascendum Kps","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dayton","addressRegion":"OH","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b508756f859dcebcc080d1bc"},"url":"https://jobsearcher.com/jobs/b508756f859dcebcc080d1bc"}}