Analytics Engineer
Lovable
Job Summary
Lovable is seeking an Analytics Engineer to manage the semantic and modeling layer of their data warehouse, transforming raw data into reliable datasets and metrics. The role involves ensuring analytical consistency and building strong foundations for self-service analytics. Lovable enables users to build software with plain English, impacting millions globally, and offers an opportunity to shape the future of digital creation within a talent-dense team in Stockholm.
Must Have
- Expertise with SQL, dbt, SQLMesh or similar tools
- Experience with data warehousing concepts and cloud warehouses (Snowflake, BigQuery, Redshift, Databricks)
- Experience with 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
Job Description
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 lets anyone and everyone build software with plain English. 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. Over 2 million people in 200+ countries already use Lovable to launch businesses, automate work, and bring their ideas to life. And we’re just getting started.
We’re a small, talent-dense team building a generation-defining company. 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:
- 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