Data Engineer
University of Maryland Global CampusAbout the role
Data Engineer
Data Strategy
Full-time, Exempt Regular, Pay Grade 4.2
Location: Hybrid
A skilled, hands-on Data Engineer responsible for designing, building, deploying, and operating enterprise data ingestion, transformation, and delivery pipelines within a Databricks Lakehouse environment. The role focuses on data integration and interoperability, enabling secure and reliable access to curated datasets for analytics, applications, and machine learning use cases.
Duties and Responsibilities:
Design, build, test, and operate scalable batch and streaming data ingestion and transformation pipelines using Databricks, Apache Spark, Delta Lake, Python, and SQL.
Implement data integration workflows that ingest and process data from diverse internal and external sources, including databases, files, REST APIs, and streaming platforms, in alignment with established architectural standards.
Develop, maintain, and document curated datasets and data products that support analytics, reporting, and downstream application and machine learning use cases.
Package, version, and deploy data pipelines using Databricks Asset Bundles, adhering to established CI/CD processes and environment promotion practices (development, test, production).
Apply data quality validation, monitoring, and observability controls to ensure data accuracy, pipeline reliability, and compliance with defined service-level objectives.
Implement and maintain access controls, authentication, and authorization using Unity Catalog in accordance with enterprise data governance and security requirements.
Monitor pipeline performance and resource utilization, perform routine tuning, and support incident resolution and root-cause analysis for production data workflows.
Collaborate with platform, analytics, and governance teams to clarify data requirements, resolve integration issues, and support data consumers.
Competencies:
Technical execution and problem solving
Attention to detail and data quality
Collaboration within cross-functional teams
Accountability for operational stability
Skills:
Databricks, Apache Spark, Delta Lake
SQL and Python
Batch and streaming ingestion patterns
Federated data access and APIs
Unity Catalog and governance
Education & Experience Requirements
Education:
Bachelor’s degree in Computer Science, Information Systems, or a related field.
Experience:
5+ years of hands-on data engineering experience supporting production data pipelines.
Preferred Experience Requirements
Education:
Master’s degree preferred.
Experience:
Large-scale governed data environments.
Certifications:
Databricks certifications preferred.
All submissions should include a cover letter and resume.
The University of Maryland Global Campus (UMGC) is an equal opportunity employer and complies with all applicable federal and state laws regarding nondiscrimination. UMGC is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, ancestry, political affiliation or veteran status in employment, educational programs and activities, and admissions.
Workplace Accommodations:
The University of Maryland Global Campus Global Campus (UMGC) is committed to creating and maintaining a welcoming and inclusive working environment for people of all abilities. UMGC is dedicated to the principle that no qualified individual with a disability shall, based on disability, be excluded from participation in or be denied the benefits of the services, programs, or activities of the University, or be subjected to discrimination. For information about UMGC’s Reasonable Workplace Accommodation Policy or to request an accommodation, applicants/candidates can contact Employee Accommodations via email at Generate a tailored application kit with a matched cover letter, interview prep, and CV highlights — in under 60 seconds. Free account required — sign up in 30sApply for this role