About the job
Why Choose Lovable?
At Lovable, we empower individuals and teams to create software using simple, plain English. Whether you are a solopreneur or part of a Fortune 100 company, our platform enables millions worldwide to turn their ideas into reality swiftly. We are pioneering a transformative approach to software development, providing you with a unique opportunity to reshape the digital landscape. Over 2 million users across 200+ countries already trust Lovable to launch businesses and streamline operations, and we’re just getting started.
As a compact yet highly skilled team based in Stockholm, we prioritize extreme ownership, rapid execution, and collaborative spirit. We are on the lookout for passionate individuals who are eager to make an impact and contribute to our journey.
Key Qualifications
Proficiency in marketing data concepts, including UTM structures and attribution methodologies.
Strong command of SQL, dbt, SQLMesh, or similar data modeling tools, including capabilities in testing, macros, and documentation.
Solid understanding of dimensional modeling, data contracts, and metrics layers.
Hands-on experience with data transformation tools such as SQLMesh and dbt.
Familiarity with event collection systems like RudderStack, Segment, Snowplow, and GA4.
Experience with cloud warehousing solutions (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase).
Strong business acumen with the ability to translate complex domain logic into scalable data models.
Your Responsibilities
Establish and manage the event taxonomy for marketing interactions, including UTMs, referrals, conversions, and campaign engagements.
Collaborate with product engineering teams to implement and validate tracking across web, app, and lifecycle channels.
Develop and maintain dimensional models (SQLMesh) for analyzing attribution, channel performance, and customer journey.
Create foundational tables for tracking attribution windows, touchpoint sequences, cohort definitions, and channel performance metrics.

