Analytics Engineer, Marketing
Our Take
Own and build the data foundation for marketing decisions at Lovable using SQL, dbt, and cloud warehouses.
What you’ll do
- Define and govern event taxonomy for marketing touchpoints
- Build and maintain dimensional models for attribution analysis
- Manage ingestion pipelines for external marketing data sources
- Monitor data quality latency and completeness across the pipeline
What they’re looking for
- Expertise with SQL and dbt or similar tools
- Understanding of dimensional modeling and data contracts
- Experience with event collection systems like RudderStack or Segment
- Familiarity with cloud warehouses such as Snowflake, BigQuery, or Redshift
As posted by Lovable
TL;DR - 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.
Why Lovable?
Lovable lets anyone and everyone build software with any language. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products - fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Lovable-built applications and websites are visited hundreds of millions of times a month, and our enterprise footprint is compounding fast. And we’re just getting started.
We’re a small, talent-dense team building a generation-defining company from Stockholm. We value extreme ownership, high velocity, and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world.
What we are looking for
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
What you will do
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
Our tech stack
We're building with tools that both humans and AI love:
Frontend: React
Backend: Golang and Rust
Cloud: Cloudflare, GCP, AWS, Many LLM providers
DevOps & Tooling: Github Actions, Grafana, OTEL, infrastructure-as-code (Terraform)
And always on the lookout for what's next!
How we hire
Fill in a short form then jump on an intro call with recruiter.
Complete the general programming exercise.
Show us how you approach problems during several technical interviews.
Tell us about your most impressive project.
About your application
Please submit your application in English - it’s our company language so you’ll be speaking lots of it if you join
We treat all candidates equally - if you’re interested please apply through our careers portal