Senior Data Engineer

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