Senior Analytics Engineer

Own the transformation layer, including dimensional models, tests, and documentation, as we stand up dbt on a new warehouse

Turn business questions into durable models. Not all work arrives fully specified, so you’ll turn ambiguity into structure and set patterns the team builds against.

Partner with finance, compliance, and product to define requirements, data definitions, and what “correct” means in our business context

Monitor what you build, catching and resolving or escalating issues before our stakeholders notice

Go a layer down into data ingestion, orchestration, or warehouse configuration when warranted, or go a layer up into analysis and decision support when needed

7+ years of combined experience across analytics engineering, data engineering, or analytics roles with substantial modeling ownership

Strong analytical SQL skills - complex joins, window functions, performance-aware queries

Data modeling / dimensional modeling fluency - you can design schemas from fuzzy requirements, not just query what exists

Transformation framework experience - dbt preferred, with Dataform, SQLMesh, or equivalent acceptable

Cloud data warehouse experience - Redshift, Snowflake, BigQuery, Databricks, or equivalent

Orchestration engine familiarity - Airflow, Dagster, Prefect, or equivalent

BI / Visualization layer familiarity - Metabase, Hex, Looker, Tableau, or similar

Engineering hygiene - Git, CI/CD, testing, documentation

Stakeholder range - you can sit with a finance or compliance lead, ask questions to get to requirements, and leave with a definition you can build against

Platform-level experience - working with tools like Terraform / infra-as-code, DMS / CDC, data lake patterns, and data observability