11 months ago
Stockholm, SwedenMid Level
Responsibilities
- Build and maintain modular, tested, and version-controlled data models.
- 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 costs.
- Automate and maintain data documentation, lineage, and governance standards.
- Develop guidelines for analytics development, data modeling, and structural conventions.
Requirements
- Expertise with SQL, dbt, SQLMesh, or similar tools for data modeling, testing, macros, and documentation.
- Experience with data warehousing concepts, cloud warehouses such as Snowflake, BigQuery, Redshift, and Databricks, and BI tools such as Looker, Tableau, Power BI, Hex, and Metabase.
- Understanding of dimensional modeling, data contracts, and metrics or semantic layers.
- Familiarity with modern ELT and orchestration workflows such as Airflow, Dagster, and Prefect.
- Strong business acumen and ability to translate domain logic into scalable data structures.
Tech Stack
Categories
Data Engineering
About Lovable
Lovable builds an AI-native software creation platform that lets people build apps and websites by chatting with AI, along with tools such as gptengineer.app. It serves solopreneurs, small businesses, and enterprise teams, and users have created over 60 million projects since its November 2024 launch, with customers including Adidas and Zendesk. The company is privately held and headquartered in Stockholm.