Analytics Engineer
AI app builder that turns natural-language prompts into full-stack web applications.
Maintainer signals as of 8/23/2026
About Lovable
Lovable (lovable.dev) is a Swedish AI software-builder platform: users describe an app in natural language and Lovable generates production full-stack code — one of the fastest-growing AI products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own the warehouse semantic and modeling layer by transforming raw data into well-defined, trustworthy datasets and metrics. You will build and maintain modular, tested, version-controlled data models; codify business logic into reusable models and metrics; define data contracts; optimize query performance and warehouse cost; and maintain documentation, lineage, and governance standards.
Requirements
- Expertise with SQL, dbt, SQLMesh, or similar tools for data modeling, testing, macros, and documentation
- Experience with data warehousing concepts, cloud warehouses, and BI tools
- Understanding of dimensional modeling, data contracts, and metrics or semantic layers
- Familiarity with modern ELT and orchestration workflows
- Business acumen and ability to translate domain logic into scalable data structures
- Submit the application in English
Responsibilities
- Build and maintain data models using modular, tested, and version-controlled practices
- Partner with domain teams to codify business logic 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
Hiring Process
1. Fill in a short form and have an intro call with a recruiter. 2. Complete the general programming exercise. 3. Participate in several technical interviews demonstrating your problem-solving approach. 4. Discuss your most impressive project.