Director, Data Product Engineering

Role Description

We are seeking a strategic and technically accomplished Director, Data Products Engineering to lead the architecture, engineering, and delivery of AI products, data products and scalable data solutions across our fintech and payment processing ecosystem.

• Drive the company’s transition toward a product-centric data operating model.
• Build trusted, reusable, scalable, and business-aligned AI/data products.
• Lead teams responsible for engineering high-quality AI/data products.
• Design scalable data architectures and enable reliable enterprise data consumption at scale.

The current ecosystem includes:

• Snowflake
• Dataiku
• dbt
• Fivetran
• Apache Iceberg on Amazon S3
• Looker & LookML
• SQL, Python
• AWS
• MySQL, PostgreSQL
• Gitlab
• Monte Carlo
• Terraform, OpenTofu
• RDS Database Insights and Datadog

This role will partner closely with Product, Engineering, Risk, and Operations teams to define enterprise data strategies, architect scalable data solutions, and operationalize high-value AI/data products that accelerate business growth and innovation.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Information Systems, or related field required; Master’s or PhD preferred.
• 10+ years of progressive leadership experience in Data, Analytics, or AI/ML organizations.
• 5+ years leading enterprise-scale analytics, data science, or AI engineering teams.
• Strong hands-on expertise in predictive analytics, machine learning, recommendation systems, decision intelligence, and AI-enabled analytics.
• Proven experience building scalable enterprise data products.
• Deep experience with modern cloud data platforms and analytical ecosystems.
• Strong technical expertise in Python, SQL, ML frameworks, and AI tooling.
• Strong executive communication and stakeholder management skills.
• Experience leading within complex, matrixed organizations.
• Exceptional communication and stakeholder management skills with ability to influence executive and technical audiences.

Requirements

• Experience within fintech, payment processing, transaction platforms, fraud analytics, or regulated financial services.
• Experience with real-time analytics and streaming architectures.
• Familiarity with MLOps platforms, feature stores, vector databases, semantic retrieval architectures, and agentic AI frameworks.
• Knowledge of PCI, SOC2, GDPR, and financial data governance requirements.
• Experience integrating predictive AI and analytical AI capabilities with broader GenAI enterprise initiatives.

Benefits

• Competitive salary and benefits with growth-company options grant.
• Fast-paced and professional work culture.
• Stock options with standard startup vesting - 1 year cliff; 4 years total.
• $50 monthly communication expense stipend to go towards your phone/internet bill.
• $250 stipend to enhance your WFH setup.
• Reimbursement for peripheral equipment: monitor (up to $400), keyboard and mouse (up to $200).
• Premium medical benefits including vision and dental (100% coverage for employees).
• Company-sponsored life and disability insurance.
• Paid parental bonding leave.
• Paid sick leave, jury duty, bereavement.
• 401k plan.
• Flexible Time Off (our team members typically take off ~3-4 weeks per year).
• Volunteer Time Off.
• 13 scheduled holidays.