Analytics Engineer

Lovable is hiring an Analytics Engineer for a remote role open to applicants in United States. Level rates it ; you can apply on Lovable.

Level's read on this job

Little AI ●○○○ is how Level rates this role: aI is not part of the work.
This is listed as a remote role.
The posting mentions Databricks, dbt and Sqlmesh among its tools and skills.
Level classes it as a mid-level role.
Lovable has 80 other open roles on Level.

AI in this role

Own data foundations, metrics, and models for GTM teams as an analytics engineer at Lovable.

databricksdbtsqlmeshsnowflakebigqueryredshiftpython

sqlanalytics-engineeringetldata-modelingbi

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.
Clear communication, collaboration, and comfort working in ambiguity.
Nice to have: experience with AI/LLM products, instrumentation, experimentation, or early-stage startups.

What you'll do

Partner with Sales and CS on data and reporting needs. Translate ambiguous business questions into structured data models, analysis and actionable insights, and data-fueled products.
Build and maintain data warehouse models that serve as the source of truth for product usage and GTM metrics.
Model CRM data, usage data, and billing data to power Sales and CS automation, CRM enrichment, lead definition and creation, and GTM tooling.
Design metrics, dashboards, and data UIs in Hex and Lovable for GTM leadership and teams to access and operationalize data.
Partner with Product and Engineering on event instrumentation and schema design.
Improve documentation, observability, governance, and data best practices.
Contribute to forecasting models, KPI definitions, and experimentation frameworks.
Own and improve data pipelines, ingestion workflows, and data quality testing.

You’ll thrive here if you

Enjoy building clean, reliable, reusable data models.
Have experience partnering closely with cross-functional GTM teams to solve real problems with data.
Prefer simplicity over complexity in data and tooling design.
Communicate clearly and proactively with technical and non-technical teams.
Take ownership, move quickly, and iterate often.
Want to help define and scale Lovable’s data foundations and culture.
Care about the rep experience and view analytics as a product.

How we hire

Fill in a short form then jump on an initial exploratory call.
Discuss your experience in more depth during a round of interviews with us.

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.

How we rate this

Analytics Engineer at Lovable rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Analytics Engineer is an open job at Lovable.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in Boston and is marked remote.
The job was posted on August 9, 2026.
Seniority: mid.
Applications are handled by Lovable. Apply on Lovable

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

SQLAnalytics EngineeringETLData ModelingBIDatabricksdbtSqlmesh

Questions you could be asked

Tell me about a project where sql was part of your work. What did you do?
Tell me about a project where analytics engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where bi was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: SQL, Analytics Engineering, ETL, Data Modeling, and BI. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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