{"schemaVersion":"jobsearcher.job.v1","id":"18e51804d71d29049d7cf917","url":"https://jobsearcher.com/jobs/18e51804d71d29049d7cf917","canonicalUrl":"https://jobsearcher.com/jobs/18e51804d71d29049d7cf917","title":"Lead Data Engineer","description":"Role: Lead Data Engineer\r\nLocation: 77380\r\nDuration: 6 Month Contract-to-hire\r\nWork Authorization: US Citizens and Green Card Holders ONLY. This role will have access to federal government information. C2C and third-party candidates are ineligible.Job Summary:\r\nWe are seeking a highly motivated Lead Data Engineer with a passion for data modeling, modern data architecture, and cloud-native engineering practices. This role is responsible for leading the technical design and implementation of enterprise data platforms while remaining hands-on in development.The ideal candidate will own solution architecture, technical implementation, delivery planning, estimations, and technical leadership while mentoring engineering team members. This individual will design scalable, reliable, and high-performance data platforms using a Databricks-native architecture built on Delta Lake, Unity Catalog, Delta Live Tables (DLT/Lakeflow Declarative Pipelines), and DBT.This position partners closely with Product, QA, Project Management, and Business stakeholders to deliver trusted, analytics-ready data products while proactively managing technical risks, dependencies, and delivery timelines.Duties/Responsibilities:\r\nLead Data Engineering & Technical Delivery\r\nOwn the end-to-end technical data engineering for enterprise data platforms.\r\nLead technical implementation while remaining hands-on with development.\r\nProvide delivery estimates, sprint planning input, and technical guidance to engineering teams.\r\nMentor and coach data engineers while establishing engineering best practices.\r\nDesign & Implement Data ModelsDesign and maintain enterprise dimensional data models that support scalable reporting and analytics.\r\nOptimize Gold-layer Delta tables and dimensional models to minimize downstream Power BI DAX complexity through upstream data transformations.\r\nApply best practices in data warehousing, semantic modeling, and modern lakehouse architecture.\r\nBuild Modern Databricks PipelinesDesign and develop modular, reusable, metadata-driven ELT pipelines using Databricks, PySpark, Delta Live Tables (Lakeflow Declarative Pipelines), Unity Catalog, and DBT.\r\nImplement scalable orchestration patterns using Databricks-native architecture.\r\nBuild robust, maintainable data pipelines following engineering best practices.\r\nDevelop Data TransformationsBuild high-performance transformations using SQL, PySpark, and DBT.\r\nImplement data quality validations, schema evolution strategies, and automated lineage.\r\nDevelop scalable transformation frameworks that support reusable engineering patterns.\r\nBuild Metadata-Driven FrameworksDesign and implement metadata-driven frameworks, code generation solutions, and agentic engineering patterns to improve engineering productivity and standardization.\r\nPromote reusable architecture patterns across data engineering initiatives.\r\nEnable Quality EngineeringPartner closely with QA teams to define testing strategies, validation criteria, and automated testing for data accuracy, completeness, and reliability.\r\nEnsure robust quality controls are incorporated throughout the engineering lifecycle.\r\nDelivery LeadershipProactively communicate technical progress, sprint status, delivery timelines, project dependencies, and technical risks to Project Management.\r\nRaise technical blockers early, escalate issues appropriately, and proactively identify delivery risks without requiring micromanagement.\r\nEnable CI/CD & DevOpsIntegrate data engineering workflows with Git and Azure DevOps for source control, automated testing, and continuous deployment.\r\nSupport AnalyticsCollaborate with analytics, BI, and business stakeholders to ensure data models are optimized for reporting and self-service analytics.\r\nTroubleshoot & OptimizeContinuously optimize pipeline performance, storage efficiency, and query execution.\r\nMonitor production environments and ensure high availability, reliability, and scalability.\r\nContinuous ImprovementStay current on Databricks, Delta Lake, DBT, and modern data engineering best practices, driving continuous improvements across the platform.\r\nRequired Skills/Abilities:10+ years of overall experience in data engineering.\r\n5+ years of hands-on Databricks experience designing and delivering enterprise data platforms.\r\nDemonstrated experience serving as a technical lead responsible for solution architecture, implementation, estimations, delivery planning, and mentoring engineering teams.\r\nExpert-level experience with Databricks, Delta Lake, Unity Catalog, Delta Live Tables (DLT/Lakeflow Declarative Pipelines), and DBT.\r\nStrong SQL and PySpark development skills.\r\nDeep experience developing scalable DBT models and transformation frameworks.\r\nProven expertise in dimensional modeling, semantic modeling, and enterprise data warehouse design.\r\nDeep experience optimizing Gold-layer Delta tables and dimensional models to simplify downstream Power BI DAX calculations through upstream transformations.\r\nExperience designing metadata-driven frameworks, code generation solutions, or agentic engineering patterns.\r\nExperience implementing enterprise data quality frameworks and partnering with QA teams to define testing strategies and validation criteria.\r\nExperience proactively communicating technical blockers, project dependencies, sprint progress, delivery timelines, and technical risks to Project Management.\r\nStrong understanding of Delta Lake architecture, performance optimization, and modern Lakehouse design principles.\r\nExperience with Git-based source control, CI/CD, and Azure DevOps.\r\nExcellent analytical, communication, leadership, and problem-solving skills.\r\nEducation and ExperienceBachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent practical experience).\r\nMinimum of 10 years of professional data engineering experience.\r\nMinimum of 5 years of hands-on Databricks development experience in enterprise environments.\r\nOur benefits include:Comprehensive medical benefits\r\nCompetitive pay\r\n401(k) retirement plan\r\n...and much more!About INSPYR Solutions\r\nTechnology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions' Privacy Policy and INSPYR Solutions' AI and Automated Employment Decision Tool Policy: https://www.inspyrsolutions.com/policies/ . By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.26-157255","company":"Inspyr Solutions","rawCompany":"inspyr solutions","city":"Spring","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-08-08T01:24:16.910Z","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":"Lead Data Engineer","description":"Role: Lead Data Engineer\r\nLocation: 77380\r\nDuration: 6 Month Contract-to-hire\r\nWork Authorization: US Citizens and Green Card Holders ONLY. This role will have access to federal government information. C2C and third-party candidates are ineligible.Job Summary:\r\nWe are seeking a highly motivated Lead Data Engineer with a passion for data modeling, modern data architecture, and cloud-native engineering practices. This role is responsible for leading the technical design and implementation of enterprise data platforms while remaining hands-on in development.The ideal candidate will own solution architecture, technical implementation, delivery planning, estimations, and technical leadership while mentoring engineering team members. This individual will design scalable, reliable, and high-performance data platforms using a Databricks-native architecture built on Delta Lake, Unity Catalog, Delta Live Tables (DLT/Lakeflow Declarative Pipelines), and DBT.This position partners closely with Product, QA, Project Management, and Business stakeholders to deliver trusted, analytics-ready data products while proactively managing technical risks, dependencies, and delivery timelines.Duties/Responsibilities:\r\nLead Data Engineering & Technical Delivery\r\nOwn the end-to-end technical data engineering for enterprise data platforms.\r\nLead technical implementation while remaining hands-on with development.\r\nProvide delivery estimates, sprint planning input, and technical guidance to engineering teams.\r\nMentor and coach data engineers while establishing engineering best practices.\r\nDesign & Implement Data ModelsDesign and maintain enterprise dimensional data models that support scalable reporting and analytics.\r\nOptimize Gold-layer Delta tables and dimensional models to minimize downstream Power BI DAX complexity through upstream data transformations.\r\nApply best practices in data warehousing, semantic modeling, and modern lakehouse architecture.\r\nBuild Modern Databricks PipelinesDesign and develop modular, reusable, metadata-driven ELT pipelines using Databricks, PySpark, Delta Live Tables (Lakeflow Declarative Pipelines), Unity Catalog, and DBT.\r\nImplement scalable orchestration patterns using Databricks-native architecture.\r\nBuild robust, maintainable data pipelines following engineering best practices.\r\nDevelop Data TransformationsBuild high-performance transformations using SQL, PySpark, and DBT.\r\nImplement data quality validations, schema evolution strategies, and automated lineage.\r\nDevelop scalable transformation frameworks that support reusable engineering patterns.\r\nBuild Metadata-Driven FrameworksDesign and implement metadata-driven frameworks, code generation solutions, and agentic engineering patterns to improve engineering productivity and standardization.\r\nPromote reusable architecture patterns across data engineering initiatives.\r\nEnable Quality EngineeringPartner closely with QA teams to define testing strategies, validation criteria, and automated testing for data accuracy, completeness, and reliability.\r\nEnsure robust quality controls are incorporated throughout the engineering lifecycle.\r\nDelivery LeadershipProactively communicate technical progress, sprint status, delivery timelines, project dependencies, and technical risks to Project Management.\r\nRaise technical blockers early, escalate issues appropriately, and proactively identify delivery risks without requiring micromanagement.\r\nEnable CI/CD & DevOpsIntegrate data engineering workflows with Git and Azure DevOps for source control, automated testing, and continuous deployment.\r\nSupport AnalyticsCollaborate with analytics, BI, and business stakeholders to ensure data models are optimized for reporting and self-service analytics.\r\nTroubleshoot & OptimizeContinuously optimize pipeline performance, storage efficiency, and query execution.\r\nMonitor production environments and ensure high availability, reliability, and scalability.\r\nContinuous ImprovementStay current on Databricks, Delta Lake, DBT, and modern data engineering best practices, driving continuous improvements across the platform.\r\nRequired Skills/Abilities:10+ years of overall experience in data engineering.\r\n5+ years of hands-on Databricks experience designing and delivering enterprise data platforms.\r\nDemonstrated experience serving as a technical lead responsible for solution architecture, implementation, estimations, delivery planning, and mentoring engineering teams.\r\nExpert-level experience with Databricks, Delta Lake, Unity Catalog, Delta Live Tables (DLT/Lakeflow Declarative Pipelines), and DBT.\r\nStrong SQL and PySpark development skills.\r\nDeep experience developing scalable DBT models and transformation frameworks.\r\nProven expertise in dimensional modeling, semantic modeling, and enterprise data warehouse design.\r\nDeep experience optimizing Gold-layer Delta tables and dimensional models to simplify downstream Power BI DAX calculations through upstream transformations.\r\nExperience designing metadata-driven frameworks, code generation solutions, or agentic engineering patterns.\r\nExperience implementing enterprise data quality frameworks and partnering with QA teams to define testing strategies and validation criteria.\r\nExperience proactively communicating technical blockers, project dependencies, sprint progress, delivery timelines, and technical risks to Project Management.\r\nStrong understanding of Delta Lake architecture, performance optimization, and modern Lakehouse design principles.\r\nExperience with Git-based source control, CI/CD, and Azure DevOps.\r\nExcellent analytical, communication, leadership, and problem-solving skills.\r\nEducation and ExperienceBachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent practical experience).\r\nMinimum of 10 years of professional data engineering experience.\r\nMinimum of 5 years of hands-on Databricks development experience in enterprise environments.\r\nOur benefits include:Comprehensive medical benefits\r\nCompetitive pay\r\n401(k) retirement plan\r\n...and much more!About INSPYR Solutions\r\nTechnology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities.Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions' Privacy Policy and INSPYR Solutions' AI and Automated Employment Decision Tool Policy: https://www.inspyrsolutions.com/policies/ . By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.26-157255","datePosted":"2026-08-08T01:24:16.910Z","dateModified":"2026-08-08T01:24:16.910Z","hiringOrganization":{"@type":"Organization","name":"Inspyr Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Spring","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"18e51804d71d29049d7cf917"},"url":"https://jobsearcher.com/jobs/18e51804d71d29049d7cf917"}}