Analytics Engineer - Finance

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 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 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

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