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We're looking for an Analytics Engineer to own the data foundation that powers marketing decisions at Lovable. You'll design event tracking, build the data models, and ensure Lovable has trustworthy, well-structured data to analyze attribution, LTV, and channel performance.
Job Responsibility:
Define and govern event taxonomy for marketing touchpoints (UTMs, referrals, conversions, campaign interactions)
Partner with product engineering to instrument and validate tracking across web, app, and lifecycle channels
Build and maintain dimensional models (SQLMesh) for attribution, channel performance, and customer journey analysis
Create foundational tables for attribution windows, touchpoint sequences, cohort definitions, and channel mapping
Manage ingestion pipelines for marketing data sources (ad platforms, affiliate networks, influencer tools)
Monitor data quality, latency, and completeness across the marketing data pipeline
Work closely with our Marketing Analyst to translate analytical needs into robust, performant data models
Requirements:
Familiarity with marketing data: UTM structures, attribution concepts, ad platform data quirks
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)
Understanding of event collection systems (RudderStack, Segment, Snowplow, GA4)
Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc)
Strong business acumen and ability to translate domain logic into scalable data structures