Analytics Engineer
Builds reliable data models, pipelines, metrics, dashboards, and automation that support Sales and Customer Success. The role requires strong SQL and analytical modeling skills, experience with cloud warehouses and ELT/ETL workflows, Python proficiency, and cross-functional communication.
About the job
Responsibilities
- Partner with Sales and Customer Success on data and reporting needs.
- Translate ambiguous business questions into structured data models, analysis, actionable insights, and data-fueled products.
- Build and maintain data warehouse models serving as the source of truth for product usage and go-to-market metrics.
- Model CRM, usage, and billing data to power Sales and Customer Success automation, CRM enrichment, lead definition and creation, and go-to-market tooling.
- Design metrics, dashboards, and data UIs in Hex and Lovable for go-to-market leadership and teams.
- Partner with Product and Engineering on event instrumentation and schema design.
- Improve documentation, observability, governance, and data practices.
- Contribute to forecasting models, KPI definitions, and experimentation frameworks.
- Own and improve data pipelines, ingestion workflows, and data quality testing.
Requirements
- Strong SQL and analytical data modeling skills, ideally with dbt or SQLMesh.
- Experience with ELT/ETL workflows and cloud data warehouses.
- Comfort with Python for automation and light data engineering.
- Experience with dashboards, business intelligence tools, and self-serve analytics.
- Clear communication, collaboration, and comfort working in ambiguity.
- Experience building clean, reliable, reusable data models.
- Experience partnering with cross-functional go-to-market teams to solve business problems with data.
- Ability to communicate clearly and proactively with technical and non-technical teams.
- Strong ownership and ability to move quickly and iterate.
Nice to Have
- Experience with AI or large language model products.
- Experience with instrumentation, experimentation, or early-stage startups.
Compensation and Benefits
- No compensation information was provided.
Skills
SQL, dbt, Sqlmesh, ELT, ETL, Snowflake, BigQuery, Redshift, Databricks, Python, Hex, Data Modeling, Data Pipelines, Data Warehousing, Data Quality Testing
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