Data Platform Engineer

University of North Carolina at Greensboro; Greensboro (NC); On-site; USD 95,000 - 135,000; Full time

Job summary

University of North Carolina at Greensboro is seeking a Data Platform Engineer to design, develop, and maintain data pipelines and Azure-based data services. The role supports decision-making across student success, academic planning, finance, and research, with a focus on data quality, usability, and performance.

The DEA team administers the enterprise data platform, ensuring stability, security, and operational continuity while leveraging Azure Data Factory, Databricks, and data lake storage.

Qualifications

• Bachelor's degree in a related discipline or 4+ years of professional experience in data engineering or related field.
• Strong SQL proficiency and experience with Azure SQL databases.
• Hands-on experience with ETL/ELT pipelines and data warehousing infrastructure.
• Experience with Databricks and Azure Data Factory or similar tools.
• Proficiency in Python for data engineering tasks.
• Git and CI/CD practices for data pipelines deployment.
• Ability to document technical solutions for stakeholders.
• Familiarity with Azure Data Lake Storage and IaC concepts.
• Knowledge of data modeling and governance concepts.
• Experience with higher education data systems (student, HR, finance).

Responsibilities

• Design, develop, and manage ETL/ELT pipelines using Azure Data Factory and Databricks.
• Ingest data from enterprise systems into the data platform and ensure quality.
• Ensure reliability, cost efficiency, and performance of data processes.
• Translate requirements into scalable data models and transformations with stakeholders.

Skills

SQL proficiency

Azure SQL

ETL/ELT pipelines

Databricks

Python

Git/CI-CD

Data modeling

Azure Data Lake

Infrastructure-as-Code

Metadata governance

Higher ed data

Education

Bachelor's degree in related discipline

Tools

Azure Data Factory

Databricks

Azure Data Lake Storage

SQL Databases

Job description

Position Number:

999509

Functional Title:

Data Platform Engineer

Position Type:

Staff

Position Eclass:

EP - EHRA 12 mo leave earning

University Information:

Located in North Carolina's third largest city, UNC Greensboro is among the most diverse, learner-centered public research universities in the state, with 18,000 students in eight colleges and schools pursuing more than 150 areas of undergraduate and over 200 areas of graduate study. UNCG continues to be recognized nationally for academic excellence, access, and affordability. UNCG is ranked No. 1 most affordable institution in North Carolina for net cost by the N.Y. Times and No. 1 in North Carolina for social mobility by The Wall Street Journal - helping first-generation and lower-income students find paths to prosperity. Designated an Innovation and Economic Prosperity University by the Association of Public and Land-grant Universities, UNCG is a community-engaged research institution with a portfolio of more than $67M in research and creative activity. The University's 2,600 staff help create an annual economic impact for the Piedmont Triad region in excess of $1B.

Primary Purpose of the Organizational Unit:

The Data Engineering and Architecture team is responsible for building and supporting UNCG's enterprise data platform. The team develops reliable data pipelines, administers cloud-based services, and maintains the infrastructure that powers analytics and reporting across the University. In addition to day-to-day engineering, the team ensures the stability, security, and operational continuity of the University's data environments.

Position Summary:

This position serves as a Data Engineer within the Data Engineering and Architecture (DEA) team in Institutional Research and Enterprise Data Management (IREDM), a division of Information Technology Services (ITS). The individual will play a key role in designing, developing, and maintaining data pipelines; supporting Azure-based data services; and ensuring data quality, usability, accessibility, and performance.
The position will leverage tools such as Azure Data Factory, Databricks, and Azure Data Lake Storage to deliver trusted data assets that support decision-making across all areas of the University, including student success, academic planning, finance, and research. This position is eligible for teleworking; however, some in-person assignments may be necessary at the supervisor’s discretion.

Minimum Qualifications:

• Bachelor's degree in a related discipline or 4+ years of professional experience in data engineering or related field or equivalent combination of education/experience.

Preferred Qualifications:

• Strong SQL proficiency (T-SQL, Spark SQL) for analytics and troubleshooting.
• Experience with Azure SQL databases / RDBMS development and performance tuning skills.
• Hands on experience developing ETL/ELT data pipelines, administering and supporting the data warehousing and analytics infrastructure.
• Demonstrated experience in Databricks and Azure Data Factory or similar technologies (examples, Microsoft Fabric, Informatica, Snowflake, Qlik).
• Proficiency in Python for data engineering.
• Experience with Git and CI/CD practices for data pipeline deployment.
• Ability to document and communicate technical solutions to technical and non-technical stakeholders.
• Familiarity with Azure Data Lake Storage.
• Exposure to Infrastructure-as-Code concepts (Databricks Asset Bundles preferred; Terraform, Bicep, or ARM templates a plus).
• Experience with data modeling (dimensional/star schema).
• Familiarity with governance and metadata management tools.
• Knowledge of higher education data systems (student, HR, finance, etc.).
• Familiarity with data architecture concepts.

Recruitment Range:

Salary commensurate with experience

Org #-Department:

Info Technology Services - 23101

Job Open Date:

09/10/2026

Open Until Filled:

Yes

FTE:

1.000

Type of Appointment:

Permanent

Number of Months per Year:

12

FLSA:

Exempt

Percentage Of Time:

65%

Key Responsibility:

Build and Maintain Data Pipelines

Essential Tasks:

• Design, develop, and manage ETL/ELT pipelines using Azure Data Factory and Databricks.
• Ingest and integrate structured and semi-structured data from enterprise systems into the data platform.
• Ensure reliability, reusability, cost efficiency, and performance of data movement and transformation processes.
• Translate institutional requirements into scalable data models and transformations in collaboration with data architecture and stakeholders.

Percentage Of Time:

15%

Key Responsibility:

Administer and Support the Enterprise Data Platform

Essential Tasks:

• Assist with configuration, monitoring, and maintenance of Azure Data Lake and Databricks services.
• Implement data quality, security, and governance standards and controls.
• Monitor workloads and optimize for performance and cost.
• Produce technical documentation and operational runbooks.
• Support internal and external data integrations by assisting with secure connectivity between enterprise applications and the data platform, in collaboration with data architecture, infrastructure and information security teams.
• Help troubleshoot data access, authentication, and connectivity issues impacting pipelines and data consumers.

Percentage Of Time:

10%

Key Responsibility:

Automation and DevOps Practices

Essential Tasks:

• Contribute to automation efforts using CI/CD pipelines and Infrastructure as Code.
• Develop and maintain reusable deployment templates and standards.
• Improve operational efficiency and reduce manual interventions through scripting and tooling

Percentage Of Time:

10%

Key Responsibility:

Other departmental duties as needed

Essential Tasks:

• Supporting the administration of Databricks.
• Helping to ensure the overall health and security of the enterprise data environment.
• Working with data architecture to develop advanced platform administration skills while contributing directly to the University's data-driven initiatives.

Physical Effort:

Hand Movement-Repetitive Motions - f, Hearing - f, Talking - f, Sitting - f

Work Environment:

Inside - c