Risk Data Engineer
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The role
Lead the Risk Data Engineering team as a hands-on technical lead responsible for architecture, modeling standards, and scalable data systems powering risk decisioning.
Design and optimize Snowflake data models and layered dbt projects (staging to marts), and manage Apache Airflow DAGs with robust CI/CD practices.
Own data modeling approaches including dimensional models, grain design, SCD strategies, and surrogate keys, while ensuring clear lineage and documentation.
Build and maintain data quality and observability through dbt tests, freshness SLAs, DataDog monitoring, and proactive incident reduction.
Lead people by hiring, onboarding, giving performance feedback, and fostering a culture of accountability and engineering excellence.
Collaborate with Risk Product Managers, Data Science, ML, and business stakeholders to translate priorities into production-ready deliverables.
Design and optimize Snowflake data models and layered dbt projects (staging to marts), and manage Apache Airflow DAGs with robust CI/CD practices.
Own data modeling approaches including dimensional models, grain design, SCD strategies, and surrogate keys, while ensuring clear lineage and documentation.
Build and maintain data quality and observability through dbt tests, freshness SLAs, DataDog monitoring, and proactive incident reduction.
Lead people by hiring, onboarding, giving performance feedback, and fostering a culture of accountability and engineering excellence.
Collaborate with Risk Product Managers, Data Science, ML, and business stakeholders to translate priorities into production-ready deliverables.
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