lead the design, development, and evolution of our enterprise analytics platform
blend hands-on technical ownership with team leadership
own critical components of our Data Vault 2.0 warehouse on Snowflake
mentor a growing team of Analytics Engineers
serve as the connective layer between raw operational data and business critical insights
work across the full analytics stack—from staging and raw vault to business vault, prime stage, and client specific information marts
deliver clean, tested, and well documented models that support finance, operations, and compliance reporting

Bachelor’s degree in a quantitative or technical field, or equivalent professional experience
5+ years of production SQL experience , including: Window functions, CTEs, Performance tuning, Scalable modeling patterns
Strong Snowflake expertise, including: Warehouse sizing and query profiling, Role‑Based Access Control (RBAC), Cost monitoring, Incremental and MERGE strategies
Hands‑on experience with dbt , including: Modular model design ref and source usage, Generic and custom tests, YAML schema configuration, CI workflows on pull requests
Solid understanding of Data Vault 2.0 or similar methodologies (e.g., Kimball, Anchor Modeling)
Proficiency with Git and GitHub workflows (branching, PRs, code reviews)
Proven ability to lead or mentor junior and mid‑level engineers
Preferred Qualifications: Experience building Streamlit or other Python‑based data applications, Familiarity with contact center platforms (Five9, inContact, Serenova, or similar), Experience using dbt Cloud for orchestration and environment management, Exposure to data integration tools such as Fivetran or Airbyte, Comfort working with semi‑structured data (VARIANT columns, LATERAL FLATTEN)

Senior Data Analytics Engineer

Key skills