{"schemaVersion":"jobsearcher.job.v1","id":"1068bd115a9e7d5ee414e166","url":"https://jobsearcher.com/jobs/1068bd115a9e7d5ee414e166","canonicalUrl":"https://jobsearcher.com/jobs/1068bd115a9e7d5ee414e166","title":"Senior Databricks Migration Engineer","description":"ECS is seeking a Senior Databricks Migration Engineer to work onsite for the US Postal Services' Inspector General's Office (OIG) at our Arlington, VA office. This role leads technical data migration efforts from legacy SQL systems, warehouses and servers to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design. This also includes building large data structures and dashboards and reporting on data migration projects.\nResponsibilities include:\nLead the technical migration from legacy SQL Server stored procedures and ADF pipelines to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design.\nTranslate traditional relational data warehousing paradigms into scalable, distributed Lakehouse frameworks (Bronze, Silver, Gold).\nDesign robust, reusable ETL/ELT frameworks using PySpark, Delta Live Tables (DLT), and Databricks Workflows.\nArchitect and refine the Gold Layer (dimensional models, star schemas) specifically to maximize Power BI performance.\nOptimize Databricks SQL Warehouses to support high-concurrency, low-latency Power BI queries (DirectQuery and Import modes).\nImplement advanced optimization techniques, including Z-Ordering, data skipping, liquid clustering, and materialized views.\nDefine and enforce governance standards for cluster sizing, auto-scaling policies, and serverless SQL compute to balance performance with cost.\nImplement proactive monitoring dashboards to track Databricks Unit (DBU) consumption and identify cost-saving opportunities.\nEstablish best practices for partition strategies and file size management within Delta Lake.\nDesign and implement a robust data security model using Unity Catalog for centralized governance.\nEnforce row-level and column-level security policies to ensure compliant data access for Power BI consumers and internal analysts.\nAlign the Lakehouse security architecture with existing enterprise Azure Active Directory (Microsoft Entra ID) and RBAC standards.\nAct as the primary technical lead, conducting dedicated pair-programming sessions, workshops, and code reviews to transition the team from SQL-centric to Spark-centric thinking.\nCreate comprehensive technical documentation, including architecture diagrams, design patterns, and optimization playbooks.\nBuild a foundational knowledge transfer framework to ensure the internal team is fully self-sufficient post-migration.\nCommunicate effectively verbally and in written form to both technical and non-technical audience\nWork in an organized fashion, completing tasks timely while paying close attention to details\nPlease Note: This position is contingent upon additional funding and requires a Public Trust background investigation. This entails an in-depth background check & either US Citizenship or Permanent Resident (Green Card) status.\nRequirements:\nBachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field\n5+ years' experience in data engineering, data system development or related roles\n5+ years' experience with cloud platforms (e.g. Azure, AWS, GCP)\n1+ year leading complex, cross-functional data projects and technical teams\nExperience with Databricks Lakehouse, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms\nExperience with data warehousing, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark\nNote: This position requires working onsite 4 days a week at out USPS customer site in Arlington, VA.\nSalary Range: $130,000 - $158,000 annually\nGeneral Description of Benefits\n\nReq Benefits:\nBenefits - Everforth ECS","company":"Everforth Ecs","rawCompany":"everforth ecs","city":"Arlington","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-08-04T21:01:45.402Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1242.00","title":"Database Administrators","slug":"database-administrators"}],"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":"Senior Databricks Migration Engineer","description":"ECS is seeking a Senior Databricks Migration Engineer to work onsite for the US Postal Services' Inspector General's Office (OIG) at our Arlington, VA office. This role leads technical data migration efforts from legacy SQL systems, warehouses and servers to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design. This also includes building large data structures and dashboards and reporting on data migration projects.\nResponsibilities include:\nLead the technical migration from legacy SQL Server stored procedures and ADF pipelines to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design.\nTranslate traditional relational data warehousing paradigms into scalable, distributed Lakehouse frameworks (Bronze, Silver, Gold).\nDesign robust, reusable ETL/ELT frameworks using PySpark, Delta Live Tables (DLT), and Databricks Workflows.\nArchitect and refine the Gold Layer (dimensional models, star schemas) specifically to maximize Power BI performance.\nOptimize Databricks SQL Warehouses to support high-concurrency, low-latency Power BI queries (DirectQuery and Import modes).\nImplement advanced optimization techniques, including Z-Ordering, data skipping, liquid clustering, and materialized views.\nDefine and enforce governance standards for cluster sizing, auto-scaling policies, and serverless SQL compute to balance performance with cost.\nImplement proactive monitoring dashboards to track Databricks Unit (DBU) consumption and identify cost-saving opportunities.\nEstablish best practices for partition strategies and file size management within Delta Lake.\nDesign and implement a robust data security model using Unity Catalog for centralized governance.\nEnforce row-level and column-level security policies to ensure compliant data access for Power BI consumers and internal analysts.\nAlign the Lakehouse security architecture with existing enterprise Azure Active Directory (Microsoft Entra ID) and RBAC standards.\nAct as the primary technical lead, conducting dedicated pair-programming sessions, workshops, and code reviews to transition the team from SQL-centric to Spark-centric thinking.\nCreate comprehensive technical documentation, including architecture diagrams, design patterns, and optimization playbooks.\nBuild a foundational knowledge transfer framework to ensure the internal team is fully self-sufficient post-migration.\nCommunicate effectively verbally and in written form to both technical and non-technical audience\nWork in an organized fashion, completing tasks timely while paying close attention to details\nPlease Note: This position is contingent upon additional funding and requires a Public Trust background investigation. This entails an in-depth background check & either US Citizenship or Permanent Resident (Green Card) status.\nRequirements:\nBachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field\n5+ years' experience in data engineering, data system development or related roles\n5+ years' experience with cloud platforms (e.g. Azure, AWS, GCP)\n1+ year leading complex, cross-functional data projects and technical teams\nExperience with Databricks Lakehouse, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms\nExperience with data warehousing, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark\nNote: This position requires working onsite 4 days a week at out USPS customer site in Arlington, VA.\nSalary Range: $130,000 - $158,000 annually\nGeneral Description of Benefits\n\nReq Benefits:\nBenefits - Everforth ECS","datePosted":"2026-08-04T21:01:45.402Z","dateModified":"2026-08-04T21:01:45.402Z","hiringOrganization":{"@type":"Organization","name":"Everforth Ecs","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Arlington","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1068bd115a9e7d5ee414e166"},"url":"https://jobsearcher.com/jobs/1068bd115a9e7d5ee414e166"}}