Data and Analytics Engineer

Virginia Tech • Blacksburg, VA

1d • $95,000 - $102,750 • Onsite

About The Position

The Data and Analytics Engineer role is responsible for designing, developing, and supporting enterprise data products, cloud data pipelines, and analytics solutions that enable institutional reporting, decision support, advanced analytics, and AI initiatives across Virginia Tech. Working within the university's modern cloud data ecosystem, the position develops scalable and secure data solutions utilizing Snowflake, AWS, Power BI, and related technologies. This role partners with business stakeholders, data stewards, and technical teams to transform institutional data into trusted, governed, and reusable data assets that support self-service analytics, operational excellence, research, and strategic decision-making. This position supports Virginia Tech's enterprise data and analytics strategy through the development and support of modern cloud-based data solutions.

Requirements

• Master's degree, or a combination of education, training, and progressive experience that equates to a Master's degree.
• Working experience designing, developing, supporting, and optimizing enterprise data, reporting, and analytics solutions.
• Significant experience with programming, scripting, or automation technologies used in data engineering and analytics environments, such as Python, SQL, or similar tools.
• Significant experience with relational databases (Oracle, Postgres, or Snowflake) and advanced SQL.
• Working experience with SQL development, data transformation, query optimization, and working with enterprise-scale relational and analytical data platforms.
• Working experience translating business requirements into scalable technical solutions that support data management, reporting, analytics, and decision-making needs.
• Working experience developing and supporting data transformation, data pipelines, or enterprise data platforms.
• Experience working with cloud-based data, analytics, or enterprise application platforms.
• Experience with data modeling, data quality management, metadata management, data governance, and enterprise data security principles.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Demonstrated ability to communicate effectively with technical and non-technical audiences and collaborate across cross-functional teams.
• Demonstrated ability to manage multiple priorities and deliver high-quality solutions in a dynamic environment.

Nice To Haves

• Experience designing, implementing, and supporting Snowflake-based data platforms in a production environment.
• Experience utilizing Snowflake platform capabilities such as Snowpark, Dynamic Tables, Streams and Tasks, Data Sharing, Horizon Catalog and Governance, and Cortex AI services.
• Experience with analytics engineering and modern data stack technologies such as dbt or similar transformation frameworks.
• Experience supporting DataOps practices, including automated testing, deployment pipelines, monitoring, observability, and operational automation.
• Experience using workflow orchestration technologies such as Apache Airflow or comparable tools.
• Experience working with infrastructure-as-code technologies such as Terraform.
• Experience supporting machine learning, predictive analytics, artificial intelligence, or generative AI initiatives.
• Experience developing enterprise data products, semantic models, or reusable analytics assets that support self-service analytics and institutional decision-making.
• Experience in integrating enterprise applications, SaaS platforms, and APIs with modern cloud data platforms.
• Experience working with higher education data domains including student, finance, human resources, advancement, research, or academic operations.
• Experience developing dashboards, reports, semantic models, or self-service analytics solutions using enterprise business intelligence platforms such as Power BI, Tableau, MicroStrategy, or comparable technologies.
• Experience using source control and collaborative development practices with tools such as Git or comparable platforms.
• Experience supporting software development lifecycles, including solution design, development, testing, deployment, documentation, and operational support activities.
• Experience developing and supporting cloud-based data platforms, data integration processes, and data pipelines using AWS or comparable cloud technologies.
• Experience developing, maintaining, and supporting data pipelines, ETL/ELT processes, and related data engineering solutions that enable reporting, analytics, and business operations.

Responsibilities

• Designing, developing, and supporting enterprise data products, cloud data pipelines, and analytics solutions.
• Developing scalable and secure data solutions utilizing Snowflake, AWS, Power BI, and related technologies.
• Partnering with business stakeholders, data stewards, and technical teams to transform institutional data into trusted, governed, and reusable data assets.
• Supporting Virginia Tech's enterprise data and analytics strategy through the development and support of modern cloud-based data solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level