Senior Engineer Data Enablement & Management, Databricks

University of Maryland Global Campus • Adelphi, MD

1d • $119,000 - $129,000 • Hybrid

About The Position

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. The role serves as a senior technical leader for enterprise data engineering, data platform operations, and advanced analytics enablement, with 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 with Data Architecture, Data Science & AI, Business Intelligence, Application Engineering, and business stakeholders to deliver scalable, secure, and trusted enterprise data capabilities.

The position is based in Adelphi, Maryland, with hybrid work and required on-site presence. It is a regular exempt, full-time role. The hiring range is $119,000–$129,000.

Applicants should submit a cover letter and resume.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, Information Technology, Computer Engineering, or a related technical discipline, or an equivalent combination of education and experience.
• At least 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 data platform initiatives.
• Skills in the Databricks Data Intelligence Platform; Apache Spark, Delta Lake, and Medallion Architecture; enterprise data engineering and pipeline development; and advanced SQL, Python/PySpark, and Scala.
• Knowledge of Databricks AI/BI dashboards, Genie Agents, Genie One, AI/ML enablement, MLflow operations, data product engineering, and semantic model development.
• Knowledge of Lakehouse, data warehouse, and data lake architecture; data integration, APIs, JDBC, cloud storage, and orchestration; and Azure and AWS data platform services.
• Knowledge of Unity Catalog, metadata, lineage, governance technologies, data quality, observability, monitoring, automation, Zero Trust security controls, and data protection.
• Skills in CI/CD, DevOps, DataOps, AIOps, MLOps, performance tuning, scalability, cost optimization, technical mentoring, and engineering governance.
• Certifications are not required.

Nice To Haves

• Master's degree in Computer Science, Information Systems, Software Engineering, Data Science, Information Technology, Computer Engineering, or a related technical discipline, or an equivalent combination of education and experience.
• At least 8 years of progressive experience in enterprise data engineering, cloud data platforms, analytics engineering, AI enablement, or Lakehouse operations.
• Experience serving as a Senior Data Engineer, Lead Data Engineer, Data Platform Engineer, Analytics Engineer, or in a similar senior technical role.
• Experience leading enterprise data modernization, Lakehouse transformation, AI enablement, and cloud migration initiatives.
• Experience integrating PeopleSoft, D2L, Salesforce, Workday, ERP, CRM, LMS, and SaaS platforms into enterprise data ecosystems.
• Experience implementing advanced governance, metadata, lineage, MDM, AI/ML, and observability capabilities.
• Experience working in higher education or similarly complex enterprise environments.
• Databricks Certified Data Engineer Professional certification.
• Databricks Certified Machine Learning Professional certification.
• Azure Data Engineer Associate certification.
• Microsoft Fabric Analytics Engineer Associate certification.
• AWS Certified Data Engineer Associate certification.
• AWS Solutions Architect Associate or Professional certification.
• ITIL Foundation or advanced ITSM certification.

Responsibilities

• 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 for scalable and reliable enterprise data services.
• Lead development and modernization of enterprise data pipelines, Lakehouse architecture components, data products, and integration capabilities for structured, semi-structured, and unstructured data.
• Guide complex migration and modernization efforts, including Redshift-to-Databricks transitions and enterprise data platform transformation initiatives.
• 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 support business intelligence, AI, machine learning, operational analytics, and self-service reporting objectives.
• Lead implementation of data quality frameworks, metadata management, lineage capabilities, observability controls, security policies, and governance standards.
• Ensure enterprise data assets meet requirements for trust, compliance, auditability, privacy, and operational reliability.
• 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.
• Mentor engineers and technical resources and contribute 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.
• Perform other duties as assigned.

Benefits

• 22 days of paid vacation, 15 days of sick leave, 3 personal days, and 16 paid holidays (17 during general election years); part-time time-off rates are prorated.
• Health care coverage, including medical with vision, dental, and prescription plans for individuals and families, effective from the first of the month following the hire date.
• Term life insurance, Accidental Death and Dismemberment Insurance, and Long-Term Disability insurance; part-time employees working less than 0.5 FTE are not eligible for LTD.
• Flexible Spending Accounts for medical and dependent care expenses.
• Retirement plan choice between the Optional Retirement Program (ORP) and the Maryland State Retirement and Pension System (MSRPS).
• Supplemental retirement plans including 401(k), 403(b), 457(b), and Roth options; the university does not provide matching funds.
• Tuition remission immediately available for Regular Exempt Staff. Spouses and dependent children become eligible for undergraduate tuition remission after two years of service; eligible part-time employees receive prorated benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior