Data and Analytics Engineer

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.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including
pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race,
religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or
disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are
an individual with a disability and desire an accommodation, please contact IT Human Resources at ithr@vt.edu during regular business hours at least 10 business days prior to the event.

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