Data & Analytics Engineer
Build and maintain core data models, pipelines, and reporting infrastructure using modern data stack tools to enable decision-making across product, ops, and GTM teams. Requires 3-6 years of production data/analytics engineering experience and expert SQL.
About the job
Responsibilities
- Build and maintain the core data models that serve as the foundation for internal analytics and client-facing insights
- Design and operate the data pipelines that transform raw sources into clean, analytics-ready tables
- Create dashboards and reporting tools that drive performance visibility and decision-making across product, ops, and GTM
- Define and enforce metric consistency across teams — including core business KPIs and product usage definitions
- Help improve and scale our analytics stack (we use GCP BigQuery and Dataform, Fivetran, Postgres, and dashboarding tools)
- Collaborate with stakeholders across teams to understand data needs and translate them into reliable systems
- Contribute to internal data culture through documentation, education, and code quality standards
Requirements
- 3–6 years of experience in data engineering, analytics engineering, or a technical data analyst role with production ownership
- Expert-level SQL and comfort working in a code-first environment (versioning, testing, documentation)
- Experience designing data models that balance usability, performance, and long-term maintainability
- Familiarity with the modern data stack — dbt, Fivetran, Airflow, GCP/AWS/Snowflake, Metabase (or equivalents)
- Strong written and verbal communication that allows you to be an effective participant in both internal debates and external relationships
- Track record of moving quickly, finding shortcuts, and going to unreasonable lengths to deliver on goals
Nice-to-Haves
- High NPS with your former teammates
Skills
SQL, dbt, Fivetran, Airflow, BigQuery, GCP, AWS, Snowflake, Metabase, Postgres, Dataform
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