Job Description

The Analytics Engineer will be responsible for supporting and developing enterprise-level reporting and analytics solutions. The employee will have strong experience with reporting tools such as MicroStrategy, data transformation using ETL tools like Talend, relational database systems such as Oracle, cloud technologies including AWS, and programming languages commonly used in the cloud, such as Python. Familiarity with both traditional and modern architectures for delivering analytics and data management solutions is essential. Strong communication and organizational skills are critical, as the engineer will work directly with business users who may not have a solid background in analytics. This position works independently and provides technical solutions to business users and data stewards.

Please note: Sponsorship is only available to candidates living in or willing to relocate to the Blacksburg, VA area.

Required Qualifications

- Master’s degree in Information Technology or related field or a combination of education, training, and experience that equates to a Master’s degree.
- Experience with cloud data pipeline tools (AWS) and on-premise solutions (Talend).
- Practical experience with Business Intelligence tools (MicroStrategy, PowerBI).
- Extensive experience with relational databases (Oracle, Postgres, Snowflake) and advanced SQL.
- Effective team collaboration and communication skills. Ability to set competing priorities and meet critical deadlines.
- Experience in full system lifecycle development, requirements gathering and implementation.
- Committed to supporting and promoting a diverse and inclusive campus community.

Preferred Qualifications

- Strong motivation to learn and adapt to new technologies independently.
- Advanced skills in creating reports, dashboards, and OLAP cubes (MicroStrategy, PowerBI).
- Deep understanding of data warehouse concepts and database maintenance.
- Experience with AWS services (Airflow, Glue) and other cloud technologies.
- Proficiency in programming languages like (Python, SAS, R, Java).
- Knowledge of devops practices (Docker, GitLab, Jenkins, Vault).
- Experience with web services and APIs for complex data sets.