About the Role
You will own the data transformation layer as dbt is introduced on a new warehouse. You will design dimensional models, tests, and documentation; translate ambiguous business questions into durable models; and establish patterns for analytics and reporting. You will work with finance, compliance, and product stakeholders to define requirements and data definitions. You will monitor models, resolve or escalate issues, and contribute to ingestion, orchestration, warehouse configuration, analysis, and decision support when needed.
Requirements
- 7+ years of combined experience in analytics engineering, data engineering, or analytics with substantial modeling ownership
- Strong analytical SQL skills, including complex joins, window functions, and performance-aware queries
- Data modeling and dimensional modeling fluency
- Experience with a transformation framework; dbt preferred, or Dataform, SQLMesh, or equivalent
- Cloud data warehouse experience, such as Redshift, Snowflake, BigQuery, Databricks, or equivalent
- Familiarity with an orchestration engine, such as Airflow, Dagster, Prefect, or equivalent
- Familiarity with BI and visualization tools, such as Metabase, Hex, Looker, or Tableau
- Experience with Git, CI/CD, testing, and documentation
- Ability to gather requirements and define data definitions with finance and compliance stakeholders
Responsibilities
- Own the transformation layer, including dimensional models, tests, and documentation
- Translate business questions and ambiguous requirements into durable data models
- Partner with finance, compliance, and product to define requirements and data definitions
- Monitor data products and resolve or escalate issues before stakeholders notice
- Contribute to data ingestion, orchestration, warehouse configuration, analysis, and decision support as needed
Hiring Process
Applied → Meet-and-Greet → Technical Interview → Final Interview