We need an analytics engineer to sit between data engineering and the analysts who depend on clean, well-modeled data every day. You'll own dbt models, define metrics consistently across the company, and make sure nobody is calculating "active users" three different ways in three different dashboards. Equal parts modeling discipline and stakeholder diplomacy, since half the job is politely explaining why two teams' numbers don't match and whose definition is actually right.
What you'll do
- Build and maintain dbt models that power dashboards and reporting
- Define and document core business metrics consistently across teams
- Partner with data engineers on upstream data quality and schema changes
- Optimize transformation performance in the warehouse (Snowflake, BigQuery)
- Support analysts and stakeholders with self-serve, well-tested data models
- Review and enforce SQL style and testing standards across the dbt project
What we're looking for
- 3+ years in analytics engineering, data engineering, or advanced analyst roles
- Strong SQL and hands-on dbt modeling experience
- Understanding of dimensional modeling and metric layer design
- Experience working in a modern data warehouse (Snowflake, BigQuery, Redshift)
- Comfortable partnering with both technical and non-technical stakeholders
- Detail-oriented approach to data testing and documentation
Nice to have
- Experience with a semantic layer tool like Cube or dbt Metrics
- Familiarity with Python for more complex transformations
- Background working directly with a BI tool like Looker
About Meridian West
About Meridian West: Meridian West provides payment and treasury infrastructure trusted by enterprise finance teams to move money reliably at scale. Headquartered in New York, the company combines regulatory, risk, and engineering expertise to support clients processing billions of dollars in annual volume across marketplaces, payroll, and insurance.
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