Homeoffice Analytics Engineer chez Virtuoso

Virtuoso® is the leading global travel agency network specializing in luxury and experiential travel. This by-invitation-only organization comprises over 1,200 travel agency locations with more than 20,000 travel advisors in 54 countries throughout North America, Latin America, the Caribbean, Europe, Asia-Pacific, Africa and the Middle East. Drawing upon its preferred relationships with more than 2,300 of the world’s best hotels and resorts, cruise lines, airlines, tour companies and premier destinations, the network provides its upscale clientele with exclusive amenities, rare experiences and privileged access. Normalized annual sales of (U.S.) $28-$32 billion make Virtuoso a powerhouse in the luxury travel industry. For more information, visit www.virtuoso.com.

The Analytics Engineer bridges the gap between data engineering and analytics. They design, build, and maintain the data models and transformation pipelines that enable reliable reporting, dashboards, and advanced analytics across the organization.      

Essential duties and responsibilities include the following. Other duties may be assigned.

1. Source System Analysis: Assess enterprise source systems, their data structures, and integration patterns to design reliable data ingestion and transformation processes.
2. Data Modeling & Organization: Build and maintain semantic data models and curated datasets for analytics and BI platforms.
3. Data Transformation: Develop efficient SQL and Python-based transformation logic (e.g., dbt or similar frameworks) to produce trusted, reusable data assets
4. Master Data Alignment: Identify and document master data systems, ensuring alignment with enterprise data management and governance practices.
5. Optimization: Optimize Snowflake queries, schemas, and pipelines for performance and cost efficiency.
6. Documentation: Create and maintain technical documentation, data dictionaries, and metadata to promote transparency and reusability.
7. Collaboration: Partner with analysts, data scientists, and business teams to translate business needs into scalable data solutions.
8. Innovation & Best Practices: Stay current with modern analytics engineering practices, advocating for automation, modular data modeling, and scalable design patterns.

Educational and Skills Requirements:

• Bachelor’s degree in related field
• 4-7 years’ work experience in related field
• Snowflake Snowpro Core
• dbt Analytics Engineering Certification
• Demonstrable experience in analytics engineering, data analysis, and data management
• Advanced SQL programming skills
• Snowflake data warehouse (schema design, optimization, warehouse management)
• Data modeling experience and knowledge of data modeling approaches (e.g., star schemas, dimensional modeling, semantic layers)
• Experience with modern data transformation frameworks, especially dbt
• Familiarity with BI platforms, with a preference for Tableau
• Documenting pipelines, data models, and metadata (for technical and non-technical audiences)
• Understanding of data management and data governance frameworks
• Demonstrable ability to collaborate across technical and business teams to define requirements and deliver solutions.
• Desired Technical Skills/Experience:
• Python
• Airflow
• Dagster
• Data Catalogs
• Innovation – Forward thinking, curious, & creative
• Intermediate Analytical Skills– Ability to collect and analyze information, problem solve, and make decisions
• Collaboration – Strong skills in inspiring the win-win-win
• Self-Starter - Ability to work independently

Travel Requirements:

• Travel is rarely required for this position (0-1 trips per year).
• Travel will be entirely domestic.

Type/Nature of Contacts:

• External: There is almost no contact outside of Virtuoso staff. Position is primarily internal facing.
• Internal: Daily contact with Virtuoso staff.

We offer a competitive salary and full benefits package, including medical/dental/vision/life, 401(k) savings plan, and more. Virtuoso is an equal opportunity employer, dedicated to promoting a diverse workforce.

Pay ranges are intended to cover roles based across the United States. An individual's base pay depends on various factors including geographical location, experience, knowledge, skills, and abilities of the applicant.