{"schemaVersion":"jobsearcher.job.v1","id":"c66fd6cf8b13f10fe4d06aa2","url":"https://jobsearcher.com/jobs/c66fd6cf8b13f10fe4d06aa2","canonicalUrl":"https://jobsearcher.com/jobs/c66fd6cf8b13f10fe4d06aa2","title":"Mid-Level Databricks Engineer","description":"We are seeking a Mid-Level Databricks Engineer to design, develop, and support scalable data solutions using Databricks and modern cloud data platforms. This role will focus on building reliable data pipelines, implementing lakehouse architectures, improving data quality, and supporting analytics and AI use cases.The ideal candidate has strong hands-on experience with Databricks, SQL, Python/PySpark, Delta Lake, and cloud data services and can work independently within established architectural and data governance standards.Key ResponsibilitiesDesign, build, test, and maintain data pipelines using Databricks, PySpark, Python, and SQLDevelop ingestion and transformation processes across Bronze, Silver, and Gold layers using Medallion Architecture principlesBuild and optimize Delta Lake tables, including data partitioning, schema management, and performance tuningDevelop batch and streaming pipelines using Databricks capabilities such as Auto Loader, Structured Streaming, Workflows, and Delta Live Tables/Lakeflow Declarative Pipelines, where appropriateIntegrate structured and semi-structured data from databases, APIs, files, cloud storage, and enterprise applicationsImplement data quality validation, reconciliation, exception handling, monitoring, and loggingWork with Unity Catalog to support data governance, access controls, metadata management, lineage, and data discoveryDevelop reusable frameworks and components for ingestion, transformation, and data validationTroubleshoot pipeline failures and performance issues and implement sustainable fixesParticipate in code reviews and follow established development, testing, security, and deployment standardsSupport CI/CD practices for Databricks development and collaborate with DevOps teams on automated deploymentsWork closely with data architects, analysts, data scientists, governance teams, and business stakeholdersCreate and maintain technical documentation, data mappings, pipeline specifications, and operational support documentationRequired Qualifications8-10 years of experience in data engineering, ETL/ELT development, or related data platform development5+ years of hands-on Databricks experience preferredStrong proficiency with:Python / PySparkSQLApache SparkDelta LakeDatabricks notebooks, jobs/workflows, and computeExperience developing scalable ETL/ELT pipelines and working with large datasetsUnderstanding of lakehouse, data warehouse, and Medallion Architecture conceptsExperience with at least one major cloud platform: Microsoft Azure, AWS, or Google CloudExperience working with Git-based source control and CI/CD processesUnderstanding of data quality, metadata, lineage, security, and data governance conceptsStrong troubleshooting, analytical, and problem-solving skillsAbility to work effectively in an Agile delivery environmentPreferred QualificationsExperience with Databricks Unity CatalogExperience with Azure Data Lake Storage, Azure Data Factory, Azure DevOps, or comparable AWS/GCP servicesExperience with Databricks Asset Bundles and infrastructure/deployment automationFamiliarity with REST APIs, JSON, Parquet, Avro, and other common data formatsExposure to Power BIExperience supporting data science, machine learning, or GenAI workloads is a plusDatabricks certification such as Databricks Certified Data Engineer Associate is a plusWhat We're Looking ForA successful candidate should be able to take a defined data requirement or technical design and independently turn it into a production-ready Databricks solution. They should be comfortable troubleshooting problems, collaborating with senior engineers and architects, and helping less-experienced developers follow good engineering practices.Leveling distinction: This is not primarily an architecture role. The emphasis is on hands-on engineering, independent delivery, code quality, data reliability, and Level 2 production support.","company":"Techstra Solutions","rawCompany":"techstra solutions","city":"Pittsburgh","state":"PA","isRemote":false,"isActive":false,"createdAt":"2026-11-05T09:40:44.962Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"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":"Mid-Level Databricks Engineer","description":"We are seeking a Mid-Level Databricks Engineer to design, develop, and support scalable data solutions using Databricks and modern cloud data platforms. This role will focus on building reliable data pipelines, implementing lakehouse architectures, improving data quality, and supporting analytics and AI use cases.The ideal candidate has strong hands-on experience with Databricks, SQL, Python/PySpark, Delta Lake, and cloud data services and can work independently within established architectural and data governance standards.Key ResponsibilitiesDesign, build, test, and maintain data pipelines using Databricks, PySpark, Python, and SQLDevelop ingestion and transformation processes across Bronze, Silver, and Gold layers using Medallion Architecture principlesBuild and optimize Delta Lake tables, including data partitioning, schema management, and performance tuningDevelop batch and streaming pipelines using Databricks capabilities such as Auto Loader, Structured Streaming, Workflows, and Delta Live Tables/Lakeflow Declarative Pipelines, where appropriateIntegrate structured and semi-structured data from databases, APIs, files, cloud storage, and enterprise applicationsImplement data quality validation, reconciliation, exception handling, monitoring, and loggingWork with Unity Catalog to support data governance, access controls, metadata management, lineage, and data discoveryDevelop reusable frameworks and components for ingestion, transformation, and data validationTroubleshoot pipeline failures and performance issues and implement sustainable fixesParticipate in code reviews and follow established development, testing, security, and deployment standardsSupport CI/CD practices for Databricks development and collaborate with DevOps teams on automated deploymentsWork closely with data architects, analysts, data scientists, governance teams, and business stakeholdersCreate and maintain technical documentation, data mappings, pipeline specifications, and operational support documentationRequired Qualifications8-10 years of experience in data engineering, ETL/ELT development, or related data platform development5+ years of hands-on Databricks experience preferredStrong proficiency with:Python / PySparkSQLApache SparkDelta LakeDatabricks notebooks, jobs/workflows, and computeExperience developing scalable ETL/ELT pipelines and working with large datasetsUnderstanding of lakehouse, data warehouse, and Medallion Architecture conceptsExperience with at least one major cloud platform: Microsoft Azure, AWS, or Google CloudExperience working with Git-based source control and CI/CD processesUnderstanding of data quality, metadata, lineage, security, and data governance conceptsStrong troubleshooting, analytical, and problem-solving skillsAbility to work effectively in an Agile delivery environmentPreferred QualificationsExperience with Databricks Unity CatalogExperience with Azure Data Lake Storage, Azure Data Factory, Azure DevOps, or comparable AWS/GCP servicesExperience with Databricks Asset Bundles and infrastructure/deployment automationFamiliarity with REST APIs, JSON, Parquet, Avro, and other common data formatsExposure to Power BIExperience supporting data science, machine learning, or GenAI workloads is a plusDatabricks certification such as Databricks Certified Data Engineer Associate is a plusWhat We're Looking ForA successful candidate should be able to take a defined data requirement or technical design and independently turn it into a production-ready Databricks solution. They should be comfortable troubleshooting problems, collaborating with senior engineers and architects, and helping less-experienced developers follow good engineering practices.Leveling distinction: This is not primarily an architecture role. The emphasis is on hands-on engineering, independent delivery, code quality, data reliability, and Level 2 production support.","datePosted":"2026-11-05T09:40:44.962Z","dateModified":"2026-11-05T09:40:44.962Z","hiringOrganization":{"@type":"Organization","name":"Techstra Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Pittsburgh","addressRegion":"PA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c66fd6cf8b13f10fe4d06aa2"},"url":"https://jobsearcher.com/jobs/c66fd6cf8b13f10fe4d06aa2"}}