Analytics Engineer

TL;DR - We are looking for analytics engineers to own the semantic and modeling layer of our warehouse by transforming raw data into well-defined, trustworthy datasets and metrics. You are obsessed with analytical consistency, designing impactful metrics, and building strong foundations for self-service analytics.

Why Lovable?
Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we're just getting started.

We're building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world.

Lovable is one of TIME's 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe's fastest-growing AI companies and one of the most ambitious places to build in this next era of software.

What we are looking for:

• Expertise with SQL, dbt, SQLMesh or similar tools (data modeling, testing, macros, docs)
• Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc)
• Understanding of dimensional modeling, data contracts, and metrics/semantical layers
• Familiarity with modern ELT and orchestration workflows (Airflow, Dagster, Prefect, etc)
• Strong business acumen and ability to translate domain logic into scalable data structures
  

What you will do:

• Build and maintain data models, following modular, tested, and version-controlled practices
• Partner with domain teams to understand business logic and codify it into reusable models and metrics
• Define and document key metrics and data contracts across domains
• Collaborate with Data Platform Engineers to optimize query performance and warehouse cost
• Automate and maintain data documentation, lineage, and governance standards
• Develop guidelines for analytics development, data modeling and structure conventions
  

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

1. Fill in a short form then jump on an intro call with recruiter.
2. Complete the general programming exercise.
3. Show us how you approach problems during several technical interviews.
4. 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