🛠 Tech Stack

💼 About This Role

You'll lead data engineering for risk and AI applications at a fintech company. You'll own data models, pipelines, and infrastructure for lending, credit, fraud, AML, and compliance domains. This role combines hands-on coding with people leadership for seasoned banking data experts.

🎯 What You'll Do

• Design and maintain integrated data models for risk domains
• Architect and manage end-to-end data pipelines with dbt, Airflow, Snowflake
• Lead data and AI projects, partnering with engineering and product teams
• Manage a team of data engineers, set coding standards and CI/CD practices

📋 Requirements

• 15+ years in data engineering, majority in US banks or financial institutions
• Deep knowledge of banking risk data domains like lending, credit, AML, KYC
• Expert-level Snowflake, dbt, and Python for data modeling and pipelines
• Hands-on experience with Airflow, MongoDB, and Terraform in production

✨ Nice to Have

• Experience in Model Risk, Integrated Risk, ERM, or Compliance Analytics at a US bank
• Familiarity with GRC platforms like ServiceNow and risk data warehouses
• Experience with LLM/AI application data pipelines and observability tooling

🎁 Benefits & Perks

• 💰 Competitive base pay range $163,200 - $280,500
• 🎯 Bonus and long term incentives
• 🏖️ Comprehensive benefits including health, wellness, and financial perks

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Phone Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min
4. 4Final Round with Director· 45 min