Senior Engineer Data Enablement & Management (Redshift/Databricks)

Senior Engineer Data Enablement & Management (Redshift/Databricks) Enterprise Architecture, Data, & Integrations US Exempt Regular Full time Stateside Exempt 4.3 Senior Engineer Data Enablement & Management (Redshift/Databricks) Central IT Admin Exempt Regular 4.3 Location: Adelphi, MD (Hybrid, On-Site Presence Required) The Senior Engineer, Data Enablement & Management is responsible for leading the design, implementation, modernization, and operational reliability of UMGC's enterprise Lakehouse and Data & AI platform. This role serves as a senior technical leader for enterprise data engineering, data platform operations, and advanced analytics enablement, providing expertise across Databricks, Delta Lake, Apache Spark, AI/BI capabilities, and cloud data architectures. The Senior Engineer leads complex data initiatives, mentors engineering staff, establishes engineering standards, and partners closely with Data Architecture, Data Science & AI, Business Intelligence, Application Engineering, and business stakeholders to deliver scalable, secure, and trusted enterprise data capabilities. Duties and Responsibilities:   Enterprise Data Engineering & Technical Leadership.  Lead the design, implementation, optimization, and operational maturity of enterprise data engineering capabilities across the Data & AI platform. Establish engineering standards, reusable frameworks, architectural patterns, automation practices, and operational procedures that support scalable and reliable enterprise data services.  Data Integration, Lakehouse & Platform Modernization.  Lead development and modernization of enterprise data pipelines, Lakehouse architecture components, data products, and integration capabilities supporting structured, semi-structured, and unstructured data. Guide complex migration and modernization efforts, including Redshift-to-Databricks transitions and enterprise data platform transformation initiatives.   AI, Analytics & Data Product Enablement.  Lead engineering efforts supporting Databricks AI/BI dashboards, Genie Agents, Genie One, semantic models, governed data products, data marts, and advanced analytics capabilities. Ensure platform capabilities effectively support business intelligence, AI, machine learning, operational analytics, and self-service reporting objectives.   Data Governance, Quality & Security Engineering.  Lead implementation of data quality frameworks, metadata management, lineage capabilities, observability controls, security policies, and governance standards. Ensure enterprise data assets meet organizational requirements for trust, compliance, auditability, privacy, and operational reliability.  Platform Operations, Reliability & Performance Optimization.  Provide senior-level engineering leadership for platform monitoring, resilience, performance optimization, troubleshooting, incident management, and operational support. Lead efforts to improve service reliability, scalability, efficiency, cost management, and operational maturity across enterprise data environments.  Mentoring, Innovation & Continuous Improvement.  Mentor engineers and technical resources while contributing to engineering standards, design reviews, technical evaluations, and platform best practices. Evaluate emerging technologies and automation opportunities that advance organizational data, AI, and analytics capabilities.  Other duties as assigned. Competencies :  Advanced data engineering and Lakehouse expertise  Technical leadership and engineering excellence  Enterprise data architecture implementation  Data quality, governance, and security awareness  Analytical thinking and complex problem solving  Systems thinking and platform optimization  Automation and operational excellence  Collaboration and stakeholder engagement  Mentoring and knowledge sharing  Accountability and results orientation  Innovation and continuous improvement  Adaptability and continuous learning.  Skills :  Databricks Data Intelligence Platform  Apache Spark, Delta Lake, and Medallion Architecture  Enterprise data engineering and pipeline development  Databricks AI/BI dashboards, Genie Agents, and Genie One  Advanced SQL, Python/PySpark, and Scala  AI/ML enablement and MLflow operations  Data product engineering and semantic model development  Lakehouse, data warehouse, and data lake architecture implementation  Data integration, APIs, JDBC, cloud storage, and orchestration  Unity Catalog, metadata, lineage, and governance technologies  Data quality, observability, monitoring, and automation  Zero Trust security controls and data protection  Azure and AWS data platform services  CI/CD, DevOps, DataOps, AIOps, and MLOps  Performance tuning, scalability, and cost optimization  Technical mentoring and engineering governance.   Education & Experience Requirements :  Education:  ​​Bachelor's Degree​ in Computer Science, Information Systems, Software Engineering, Data Science, Information Technology, Computer Engineering, or a related technical discipline or equivalent combination of education and experience.  Experience:   5+ years of progressive experience in data engineering, data platform engineering, analytics engineering, database engineering, or related disciplines.  Experience leading enterprise-scale Databricks, Delta Lake, Spark, and Lakehouse implementations.  Experience designing and operating enterprise data pipelines, governed data products, and analytical platforms.  Experience supporting Databricks AI/BI capabilities, semantic models, Genie Agents, and advanced analytics solutions.  Experience implementing enterprise data governance, observability, security, and operational controls.  Experience leading modernization, migration, automation, and platform optimization initiatives.  Experience mentoring engineers and serving as a senior technical resource for