Data Engineer, Darden School of Business

University of Virginia - Charlottesville, VA

Full-time

Charlottesville, VA

Educational Services

About the position

The University of Virginia Darden School of Business, recognized as one of the premier business schools globally, is seeking a highly skilled and motivated Data Engineer to join its Strategic IT Data & Analytics team. This position is pivotal in building and maintaining the data infrastructure that supports the school's data-driven initiatives. The Data Engineer will be responsible for ensuring the efficient extraction, loading, and transformation (ELT) of data from various sources into our cloud data environments, which is essential for supporting analytics and reporting needs. The ideal candidate will possess hands-on experience with ELT processes, particularly in Databricks, and should have a strong analytical mindset. A passion for higher education and a collaborative work ethic are essential traits for success in this role. While the position is primarily based in Charlottesville, Virginia, the Darden School of Business offers flexibility, allowing the employee to work remotely for most of the year. However, it is required that the employee be onsite for one week every quarter to ensure alignment with the team and ongoing projects. In this role, the Data Engineer will develop and implement efficient and scalable metadata-driven data pipelines using cloud-based ELT pipelines. Collaboration with cross-functional teams, including data analytics developers, functional analysts, and business stakeholders, will be crucial to understand data requirements and ensure smooth integration of data sources. The Data Engineer will also be responsible for building models, data integration workflows, and data transformation processes that support data analysis, reporting, and visualization. Continuous improvement and innovation in data engineering practices will be a key focus, as the individual stays current with emerging trends and technologies in the field.

Responsibilities

• Develop and implement efficient and scalable metadata-driven data pipelines using cloud-based ELT pipelines to support our data processing and analytics needs.
• Collaborate with cross-functional teams, including data analytics developers, functional analysts, and business stakeholders, to understand data requirements and ensure the smooth integration of data sources.
• Build models, data integration workflows, and data transformation processes to support data analysis, reporting, and visualization.
• Develop, orchestrate, and maintain data pipelines and data processing workflows, ensuring data quality, reliability, and performance.
• Develop and maintain continuous integration/continuous deployment (CI/CD) pipelines for data engineering artifacts.
• Identify and address performance bottlenecks and data quality issues in collaboration with the data operations team.
• Monitor and troubleshoot data pipelines to ensure high availability, scalability, and optimal performance.
• Develop and maintain integrations between the cloud data platform and the enterprise data governance platform.
• Assist in implementing data governance and security measures to ensure compliance with data protection regulations and industry best practices.
• Stay current with emerging trends, design patterns, and technologies in data engineering and cloud-based data processing to drive continuous improvement and innovation within the organization.

Requirements

• Bachelor's degree in Computer Science, MIS, Computer Engineering, Business Administration, or related discipline with at least five years of professional work experience. Relevant experience may be considered in lieu of a degree. A Master's degree is a plus.
• Certification as Databricks Data Engineer Associate or Professional, or demonstrated progress to complete certification within six months of joining.
• Proven work experience as a Data Engineer or in a similar role, with a focus on developing and implementing data pipelines and ETL/ELT processes.
• Strong proficiency in working with Databricks and Unit strongly preferred.