Senior Engineer Data Enablement & Management, Databricks

University of Maryland Global Campus • Adelphi, MD

1d • Hybrid

About The Position

The Senior Engineer, Data Enablement & Management leads the design, implementation, modernization, and operational reliability of UMGC’s enterprise Lakehouse and Data & AI platform. The role provides senior technical leadership across enterprise data engineering, data platform operations, and advanced analytics, with expertise in 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 leads development and modernization of data pipelines, Lakehouse components, data products, and integrations for structured, semi-structured, and unstructured data. It supports enterprise platform modernization and migrations, including Redshift-to-Databricks transitions, and enables Databricks AI/BI dashboards, Genie Agents, Genie One, semantic models, governed data products, data marts, and advanced analytics.

The Senior Engineer also leads data quality, metadata, lineage, observability, security, and governance initiatives, and provides engineering leadership for monitoring, resilience, performance, troubleshooting, incident management, and operational support. The role mentors engineers, contributes to standards and design reviews, and evaluates emerging technologies and automation opportunities. Other duties as assigned.

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; 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; 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; and 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 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 within 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 integrations 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 organizational requirements for trust, compliance, auditability, privacy, and operational reliability.
• Provide senior engineering leadership for platform monitoring, resilience, performance optimization, troubleshooting, incident management, and operational support.
• 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); time off is prorated for part-time employees.
• 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 Maryland State Retirement and Pension System (MSRPS); the university does not provide matching funds.
• Supplemental retirement plans including 401(k), 403(b), 457(b), and Roth options.
• Tuition remission immediately available for Regular Exempt Staff; spouses and dependent children are eligible for undergraduate tuition remission after two years of service. For part-time employees working at least 50 percent of the time, tuition remission is prorated.

What This Job Offers

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