Analytics Engineer
- Salary
- ₹15–26 LPA
- Location
- Boston, US
- Experience
- Intermediate
About company
TL;DR - We’re seeking an Analytics Engineer to own the data foundations that fuel the GTM teams: building reliable models, shaping metrics, powering automation, and turning raw data into the insights and data products that drive Sales and Customer Success. Why Lovable? Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we’re just getting started. We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world. Lovable is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software. What we're looking for We’re looking for an Analytics Engineer with a background in Data Engineering or Analytics Engineering who operates as a true full-stack analyst, owning everything from raw data to insights to operationalization. You bring: Strong SQL and analytical data modeling skills (ideally dbt or SQLMesh). Experience with ELT/ETL workflows and cloud warehouses (Snowflake, BigQuery, Redshift, Databricks). Comfort with Python for automation and light data engineering. Experience with dashboards, BI tools, and self-serve analytics.