Job Description

Position Overview:
The Data Engineer develops, maintains, and supports cloud-based data integration solutions that enable reliable, secure, and timely data exchange across institutional systems and external partners. This position designs and supports automated data pipelines, monitors data integration processes, troubleshoots technical issues, and contributes to the ongoing improvement of the organization’s data platform. The Data Engineer collaborates with technical teams and stakeholders to understand business and data requirements and deliver effective, scalable data solutions.

Why Work at UMBC?
UMBC offers competitive compensation. This role starts at $90,000 and has over 4 weeks of vacation for regular full time roles. Tuition remission is also available.

Telework:
A hybrid telework schedule may be available.

Responsibilities:
Design, develop, configure, and support cloud-based data pipelines that integrate data from internal and external sources into the organization’s data warehouse and data lake environments.
Build, schedule, monitor, and troubleshoot automated data processes to ensure data is delivered accurately, securely, and on time.
Apply data security, access, and governance practices to protect institutional data and maintain data integrity throughout the integration process.
Support data engineering projects by planning and coordinating activities, tracking deliverables, resolving technical issues, and ensuring solutions meet business and operational needs.
Collaborate with technical teams, business stakeholders, and external partners to understand data requirements, establish priorities, communicate progress, and resolve integration issues.
Identify and implement improvements to data integration processes, automation, monitoring, documentation, and operational procedures to increase reliability, efficiency, and scalability.
Required Minimum Qualifications:
Bachelor's degree prefereably in Computer Science, Information Systems, or related field.
1 year of experience in a professional capacity using cloud-native data engineering tools and services (e.g., Lambda, Python, SQL, Glue, Redshift, Event Bridge, AWS Secrets, Athena Apache Spark, Iceberg file formats and related technologies) to ingest, transform, and deliver data.