Remote Automation Engineer Jobs in Draper, VA (NOW HIRING)

Job Description

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.

Required Qualifications

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.

Preferred Qualifications

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.

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Regular

Salary Information

$95,000 - $102,750

Hours per week

40

Review Date

8/18/26

Additional Information

The successful candidate will be required to have a criminal conviction check.

Sponsorship is not available for this position. 

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance.  These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.