What is an Analytics Engineer?
An analytics engineer builds and maintains the data models, transformations, and infrastructure that power analytics at a company. They sit between data engineering (building raw data pipelines) and data analysis (consuming clean data) — using tools like dbt to create reliable, tested, documented data models that analysts and data scientists can trust. Analytics engineers emerged as a distinct role with the rise of the modern data stack.
At what stage should you hire an Analytics Engineer?
Series A through Series C, when the analytics foundation has grown complex enough that raw data transformations are becoming brittle, undocumented, and hard to maintain. The signal: analysts are spending significant time cleaning data instead of analyzing it, or different teams are computing the same metrics differently and arriving at conflicting numbers.
Common titles for this role
- Analytics Engineer
- Data Transformation Engineer
- Analytics Platform Engineer
- Senior Analytics Engineer
- dbt Analytics Engineer
What does an Analytics Engineer do at a startup?
- Build and maintain dbt data models: staging, intermediate, and mart layers
- Define and document company metrics: ensure consistent metric definitions across tools
- Write data quality tests and monitor data pipeline health
- Optimize query performance in the data warehouse
- Partner with data engineers on data ingestion pipelines and schema design
- Enable self-serve analytics: build clean, documented models that analysts can query confidently
- Maintain the data catalog and promote data discoverability
Key skills and qualifications
- Strong SQL expertise — this is the core tool of the analytics engineer
- dbt proficiency: building models, writing tests, using packages, dbt Cloud or Core
- Data warehouse experience: Snowflake, BigQuery, or Redshift
- Software engineering practices applied to data: version control, testing, documentation
- Understanding of the analytics engineering workflow: bronze/silver/gold or staging/intermediate/mart
- Python for scripting, data validation, and extending dbt functionality
Why hire your Analytics Engineer through RFS?
- Analytics engineer is a relatively new and specialized role — we know the skill set and how to evaluate it
- 29-day average time to hire — analytics engineering searches are niche; our network is an advantage
- Pre-vetted for dbt depth and modern data stack experience
- 300+ placements at VC-backed companies across data, engineering, and analytics functions
- No upfront fees
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