Lovable
Analytics Engineer, Finance
Stockholm, SwedenApplications closedFinanceBillingSubscriptions
Our Take
Own and build the data foundation for financial reporting at Lovable using SQL, dbt, and cloud warehouses.
What you’ll do
- Build and maintain dimensional models (SQLMesh) for revenue recognition
- Manage ingestion pipelines for financial data sources
- Reconcile data across systems to ensure accuracy
- Define and document business logic for financial metrics
What they’re looking for
- Familiarity with subscription/SaaS metrics
- Experience working with billing and payment data
- Expertise with SQL, dbt, or similar tools
- Understanding of dimensional modeling
As posted by Lovable
TL;DR - We're looking for an Analytics Engineer to own the data foundation that powers financial reporting and analysis at Lovable. You'll build the models that connect billing, subscriptions, and revenue data to ensure Finance has accurate, auditable data for reporting, forecasting, and decision-making.
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 subscription/SaaS metrics (MRR, ARR, churn, LTV, cohort analysis)
Experience working with billing and payment data (Stripe, Chargebee, or similar)
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)
Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc)
Attention to detail and understanding of why accuracy matters for financial data
What you will do
Build and maintain dimensional models (SQLMesh) for revenue recognition, subscription metrics, and financial reporting
Create foundational tables for MRR/ARR, churn, expansion, contraction, and cohort-based revenue analysis
Manage ingestion pipelines for financial data sources (Stripe, billing systems, payment processors)
Reconcile data across systems to ensure accuracy between source of truth and reporting layers
Define and document business logic for financial metrics (recognized revenue, deferred revenue, bookings)
Monitor data quality and implement validation checks for financial data integrity
Partner with Finance to translate reporting requirements into reliable, well-structured 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