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We're looking for an Analytics Engineer to own the data foundation that powers financial reporting and analysis at Lovable. You'll build the models that connect billing, subscriptions, and revenue data to ensure Finance has accurate, auditable data for reporting, forecasting, and decision-making.
Job Responsibility:
Build and maintain dimensional models (SQLMesh) for revenue recognition, subscription metrics, and financial reporting
Create foundational tables for MRR/ARR, churn, expansion, contraction, and cohort-based revenue analysis
Manage ingestion pipelines for financial data sources (Stripe, billing systems, payment processors)
Reconcile data across systems to ensure accuracy between source of truth and reporting layers
Define and document business logic for financial metrics (recognized revenue, deferred revenue, bookings)
Monitor data quality and implement validation checks for financial data integrity
Partner with Finance to translate reporting requirements into reliable, well-structured data models
Requirements:
Familiarity with subscription/SaaS metrics (MRR, ARR, churn, LTV, cohort analysis)
Experience working with billing and payment data (Stripe, Chargebee, or similar)
Expertise with SQL, dbt, SQLMesh or similar tools (data modeling, testing, macros, docs)
Understanding of dimensional modeling, data contracts, and metrics/semantical layers
Hands-on experience with data transformation tools (SQLMesh, dbt, or similar)
Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc)
Attention to detail and understanding of why accuracy matters for financial data