Senior Data Engineer

About the role

ABOUT VOICEMOD ✨

At Voicemod, our mission is to enable people to supercharge their voice wherever they communicate, fostering self-expression and belonging. We create audio tools that let gamers, streamers, and content creators shape their online identity with voice changers, soundboards, and real-time effects. Millions of people use Voicemod every day to enhance their interactions and have fun.

We’re a team of 90+ people working remotely, from our Valencia HQ, or from our coworking space in Barcelona. We’re passionate about pushing the boundaries of audio and building products that make digital spaces more expressive and playful. At Voicemod, we care deeply about our people and users — if you share our passion, we’d love to meet you!

OUR VALUES 💜

At Voicemod, our values are more than just words — they shape how we work every day:

🚀 Be Brave – Courage drives progress. 🏆 Show Ownership and Accountability – Impact begins with ownership. 🎸 Embrace Passion at Play – Passion builds success. 🤝 Grow Together – Go further by growing together.

ABOUT THE ROLE 💡

We are looking for a Senior Data Engineer to help make Voicemod's analytics AI-driven. Your mission is to build AI-ready data: the best data and context, so AI can get the most out of it.

This is a full-stack role. You will design event tracking plans with product teams, build and run the ingestion pipelines that land our data in Snowflake, and model it in dbt. Just as important, you will make that data AI-ready, with the metric definitions, documentation and semantic models that let AI tools and people alike get accurate, trustworthy answers.

Our stack: We run a hybrid model: Amplitude for real-time product analytics, and Snowflake with dbt for slower, exact reporting. Data lands through Weld, Stitch and dltHub, orchestrated with Airflow.

WHAT YOU’LL DO 🎯

- AI-ready data: design the semantic layer and metadata (descriptions, metric definitions, business context) that let AI tools query our data accurately, and help move our reporting beyond Looker.

- Data stewardship: own data quality tests, metric definitions and documentation, so both people and AI agents can find and trust the right data.

- dbt modelling: develop dbt models that turn raw data into reliable, documented datasets ready for final consumption.

- Keep real-time (Amplitude) and exact (Snowflake and dbt) reporting consistent, so the same metric means the same thing in both places.

- Build, run and monitor ingestion pipelines with Weld, Stitch and dltHub, bringing product, payments, marketing and third-party data into Snowflake.

- Orchestrate pipelines in Airflow, with alerting and clear recovery paths.

WHAT YOU’LL NEED ✅

- Solid experience in Data Engineering or Analytics Engineering, with advanced SQL skills.

- Hands-on experience with dbt and a cloud data warehouse, ideally Snowflake.