Analytics Engineer

Role

As an Analytics Engineer at Lovable you will own the end-to-end data foundation for GTM teams: build and maintain warehouse models, design metrics and dashboards, enable CRM and usage-derived automation, and turn ambiguous business questions into structured, operational data products.

Key Responsibilities

• Partner with Sales and Customer Success to translate business needs into data models, analyses, and actionable insights.
• Build and maintain data warehouse models as the single source of truth for product usage and GTM metrics.
• Model CRM, usage, and billing data to support CRM enrichment, lead creation, and GTM tooling.
• Design metrics, dashboards, and data UIs in Hex and Lovable for leadership and day-to-day use.
• Collaborate with Product and Engineering on event instrumentation and schema design.
• Improve documentation, observability, governance, and data quality testing for pipelines and ingestion workflows.
• Contribute to forecasting models, KPI definitions, and experimentation frameworks.

Requirements

• Strong SQL skills and analytical data modeling experience.
• Experience with ELT/ETL workflows and cloud data warehouses.
• Comfort using Python for automation and light data engineering tasks.
• Experience building dashboards, BI tools, and enabling self-serve analytics.
• Clear communication and collaboration skills; able to work in ambiguity and partner cross-functionally.
• Product-minded approach to analytics and ownership of data as a product.

Nice to have

• Experience with dbt or SQLMesh.
• Experience with AI/LLM products, instrumentation, experimentation, or early-stage startups.

Hiring process (summary)

• Short form and an exploratory call.
• Interview round(s) to discuss experience.
• A 1–2 day workshop (remote or onsite) to evaluate fit and working style.