Senior Data Engineer

The role

You will own the full data stack including ingestion, transformation, warehouse architecture, and pipeline reliability. You will work at the intersection of a quantitative strategy team and an engineering organization.

What you will do

• Architect and own the data warehouse.
• Design and optimize the BigQuery environment.
• Build and maintain transformation layers using dbt.
• Build and manage robust data pipelines with orchestration, monitoring, alerting, and failure recovery.
• Design and implement streaming infrastructure for live game economics, real-time risk signals, and in session player behavior.
• Close the loop between model outputs and production systems via reverse ETL.
• Build testing, validation, and monitoring frameworks for data quality.
• Partner with DS and engineering teams.

Required qualifications

• Strong software engineering fundamentals.
• Deep experience with SQL and Python in production data contexts.
• Hands-on experience with data warehousing (BigQuery, Snowflake, Redshift, or similar).
• Experience building and operating data pipelines with orchestration tooling (Airflow, Dagster, Prefect, or similar).
• Understanding of data modeling patterns (dimensional modeling, slowly changing dimensions, incremental materialization).
• Ability to work independently and make sound architectural decisions.

Nice to have

• dbt strongly preferred
• Experience with streaming/real-time data systems (Kafka, Pub/Sub, Flink, or similar)
• Familiarity with analytics engineering and the modern data stack (Fivetran, Statsig, or similar tools)
• Exposure to quantitative or financial data environments where correctness and latency matter
• Experience being an early or first data engineering hire

Benefits

• Competitive salary
• $400/mo lunch credit
• healthcare
• vision
• dental
• 401k

About the company

Triumph is a high growth consumer platform touching gaming, finance, and social. It is a small, high-impact engineering team with 16x year over year growth.