Data Platform Engineer

Women In Science; Greensboro (NC); Hybrid; USD 95,000 - 130,000; Full time

Job summary

University of North Carolina Greensboro (UNCG) is seeking a Data Engineer within the Data Engineering and Architecture (DEA) team to design, develop, and maintain data pipelines using Azure Data Factory, Databricks, and Azure Data Lake Storage. The role focuses on ensuring data quality, usability, accessibility, and performance across university analytics and reporting needs.

You will work on trusted data assets supporting student success, planning, finance, and research, with teleworking

Qualifications

• Strong SQL proficiency (T-SQL, Spark SQL) for analytics and troubleshooting.
• Experience with Azure SQL databases / RDBMS development and performance tuning.
• 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.
• 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 (Terraform, Bicep, or ARM templates).
• 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.

Responsibilities

• Design, develop, and maintain data pipelines across Azure-based services.
• Support Azure-based data services and ensure data quality, usability, and performance.
• Collaborate with stakeholders to translate requirements into scalable data solutions.
• Maintain and improve data warehouse infrastructure and analytics tooling.
• Leverage Databricks and Azure Data Factory to deliver trusted data assets.

Skills

SQL proficiency

Python

Git & CI/CD

Data pipeline design

Communication with stakeholders

Azure data services

Databricks

Azure Data Factory

Azure Data Lake Storage

Data modeling

Governance & metadata

Education

Bachelor's degree or equivalent experience

Tools

Azure SQL

Databricks

Azure Data Factory

Azure Data Lake Storage

Terraform/Bicep/ ARM templates

Job description

University of North Carolina

Greensboro, NC

Job Description

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

Additional Required Certifications, Licensures, and Certificates

• 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.