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# Founding Analytics Engineer

- **Company:** fonio GmbH
- **Location:** Wien, Austria
- **Experience:** Experienced
- **Salary:** €65,000.0 - €130,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Extract Transform Load (ETL), Data Warehousing, Raw Data, Standard Sql, Snowflake, Claude
- **Published:** October 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=89b10309ff052d97

## About the Role

* 3-5 years of hands-on experience with a modern data warehouse such as Snowflake.
 * Experience with ETL and reverse-ETL tools.
 * Strong SQL and dbt experience.
 * You're comfortable doing both the engineering and the modelling.
 * You're a super dedicated hustler: you own it end to end and move fast without waiting for a team around you.
 * You'd rather automate a task than do it by hand twice.

## Description

Fonio is Europe's market leader for AI phone agents for SMBs. Now we're expanding globally and into new products.
We move fast, take ownership, give direct feedback, and avoid politics and unnecessary meetings., * Build and own Fonio's data foundation, from the raw data to the models.

 * Combine data from our own systems and third-party tools in one warehouse.
 * Build the models the business runs on, starting with CLTV.
 * Make the data easy for anyone in the company to use, and make sure everyone gets the same answer., * Set up and run the data warehouse (e.g. Snowflake) using off-the-shelf tools: buy the plumbing, build the models.
 * Build and maintain ETL and reverse-ETL pipelines, choosing cost-effective tools (e.g. Weld over Fivetran).
 * Own the modelling layer in dbt (or similar), and automate as much as possible.
 * Build a cohort-based CLTV model first, then other core models such as retention and payback.
 * Define the key metrics (CAC, CLTV, churn, activation) once, and document them as the single source of truth.
 * Open the warehouse to the team so anyone can query it and build dashboards with Claude, with the right access controls in place.
 * Set up data tests and monitoring so people can trust the numbers.
 * Work closely with the founders and the marketing team, turning business questions into models.