The University of Virginia Darden School of Business, one of the world’s leading business schools, seeks a highly skilled and motivated Data Engineer/Senior Data Engineer to join its Strategic IT Data & Analytics team. This role will play a crucial role in building and maintaining our data infrastructure, ensuring the efficient extraction, loading and transformation (ELT) of data from various sources into our cloud-based data environments. The ideal candidate should have hands-on experience with ELT processes in cloud data platforms such as Databricks, Snowflake, or Microsoft Synapse. If you are passionate about data engineering, have strong analytical skills, a passion for higher education and enjoy working in a collaborative environment, we would love to hear from you. While the position is based in Charlottesville, VA, we offer the opportunity for the employee to work remotely for the majority of the year. However, we do require that the employee be onsite for one week every quarter.
To be considered for a data engineer role, responsibilities include:
Assist in designing and implementing efficient and scalable data pipelines using cloud-based ELT technologies (Microsoft Data Factory, Databricks, etc.) to support our data processing and analytics needs.
Collaborating 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.
Assist in building models, data integration workflows, and data transformation processes to support data analysis, reporting, and visualization.
Developing, maintaining and orchestrating data pipelines and data processing workflows, ensuring data quality, reliability, and performance.
Identifying and addressing performance bottlenecks and data quality issues in collaboration with the data operations team.
Monitoring and troubleshooting data pipelines to ensure high availability, scalability, and optimal performance.
Assist in implementing data governance and security measures to ensure compliance with data protection regulations and industry best practices.
Keeping up-to-date with emerging trends, design patterns and technologies in data engineering and cloud-based data processing to drive continuous improvement and innovation within the organization.
In addition to the above, Senior Data Engineer responsibilities include:
Utilizing more fully developed technical skills and emerging advanced skills, to take on data engineering projects that are more complex.
Designing scalable and efficient data architectures.
Optimizing data pipelines, data integration workflows, and data transformation processes
Leading the implementation of data governance practices, ensuring compliance with data protection regulations and industry standards.
Providing guidance and mentorship to junior team members
Education and Professional Experience:
Data Engineer – Bachelor’s degree in Computer Science, MIS, Computer Engineering or related discipline with at least five years of directly related experience. Relevant experience may be considered in lieu of a degree.
Senior Data Engineer – Bachelor’s degree in Computer Science, MIS, Computer Engineering or a related discipline with at least seven years of directly related experience. Relevant experience may be considered in lieu of a degree.
Certification in Databricks and/or Snowlake strongly preferred, or demonstrated progress to complete certification.
Proven work experience as a Data Engineer or in a similar role, with a focus on developing and implementing data pipelines and ELT processes.
Strong proficiency in working with cloud-based data platforms such as Microsoft Synapse, Databricks, or Snowflake, and experience with ELT processes.
Hands-on experience with programming languages such as SQL, Python, and Scala for data manipulation, scripting, and automation.
Proficiency in data modeling, database design, and SQL optimization techniques.
Solid understanding of data warehousing concepts, dimensional modeling, and data integration techniques.
Familiarity with data governance, data security, and privacy practices.
Strong analytical and problem-solving skills, with the ability to work with large and complex datasets.
Knowledge and experience working with APIs and web services.
Familiarity with incorporating continuous integration/continuous deployment (CI/CD) development practices into data engineering workflows.
Experience with big data technologies (e.g., Hadoop, Spark) and distributed computing frameworks is a plus.
Excellent communication and collaboration skills, with the ability to work effectively in a team-oriented environment.
To Apply:
Please apply through Workday, and search for R0051124. Internal applicants must apply through their UVA Workday profile by searching ‘Find Jobs’.
Complete the application, and upload the following Required materials:
CV/Resume
Cover letter
Please note: Multiple documents can be submitted into the CV/Resume field. Alternatively, merge all documents into one PDF for submission. Applications that do not contain all required documents will not receive full consideration.
For questions about the application process, please contact Jon Freeman, Academic Recruiter [email protected].
For more information about UVA and the Charlottesville community please see http://www.virginia.edu/life/charlottesville and https://embarkcva.com/.
The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person’s perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.
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