About the role
We are looking for a Senior Data Engineer with 4–8+ years of experience to join Triumph Labs as their first dedicated data engineering hire. This is a rare opportunity to own the entire data stack from scratch at a hypergrowth consumer platform processing billions in volume — you'll set the architecture, choose the tooling, and build the foundation that the quant and data science teams depend on.
What will you be doing?
- Architect and own the full data warehouse (BigQuery) — modeling, schemas, performance, and reliability as data scales with explosive user growth
- Build and maintain dbt transformation layers end-to-end, including testing, documentation, and CI/CD pipelines
- Design and operate robust pipeline orchestration with monitoring, alerting, and failure recovery (nothing breaks silently)
- Implement real-time/streaming infrastructure for live game economics, risk signals, and in-session player behavior
- Partner closely with the data science and quant teams to close the loop between model outputs and production systems
Key Requirements
- Proven experience as a first or early data engineering hire — you've built a data stack from scratch, not just inherited one
- Deep hands-on production experience with dbt + BigQuery (or Snowflake/Redshift), owning models and CI/CD end-to-end
- Strong pipeline orchestration experience with Airflow, Dagster, or Prefect including monitoring and failure recovery
- Background at a high-growth consumer or fintech startup where data correctness and latency were business-critical
- Able to make sound architectural decisions independently — thrives with autonomy and minimal handholding