Note: The job is a remote job and is open to candidates in USA. PayNearMe builds technology that simplifies how businesses and customers make and receive payments through its payment experience platform. The Director, Data Product Engineering will lead the architecture, engineering, and delivery of AI products, data products, and scalable data solutions, while establishing a product-centric data operating model and leading high-performing data engineering teams.
Responsibilities
- Collaborate with the Data leadership team on the refinement of our strategy for Data Products Engineering and scalable data product delivery with a focus on enabling/building AI-powered solutions
- Establish a product-centric operating model for data capabilities, emphasizing:
- Reusable and governed data products with a focus on accelerating AI/data products
- Domain-oriented ownership
- Data contracts and SLAs
- Product lifecycle management
- Discoverability and interoperability
- Standardized business metrics and semantic models
- Partner with business and technology stakeholders to identify, prioritize, and deliver strategic data products aligned to enterprise goals
- Drive the creation of scalable enterprise data assets supporting:
- Fraud and risk intelligence
- Transaction analytics
- Merchant and customer insights
- Financial and operational reporting
- AI/ML enablement
- Regulatory and compliance requirements
- Lead strategic architecture and engineering decisions for domain data solutions and our modern cloud-based analytical AI/data platform expansion
- Design scalable, resilient, and AI-ready data architectures that support high-volume transactional processing and analytical workloads
- Collaborate with Data team leadership on enterprise standards for:
- Data modeling and semantic design
- ELT/ETL frameworks
- Data orchestration
- Data quality and observability
- Metadata management and lineage
- Data governance and security
- Performance optimization and scalability
- Architect data solutions that enable trusted, near real-time, and self-service access to enterprise data
- Drive architectural alignment across operational systems, analytics platforms, AI/ML environments, and reporting ecosystems
- Partner with Architecture, Cloud Engineering, and Security teams to ensure long-term AI and data product scalability, interoperability, and compliance
- Lead and scale high-performing Data Product Engineering team responsible for domain AI product and data product delivery
- Oversee development and operationalization of scalable cloud-native data pipelines and data services
- Drive modernization of legacy data workflows and platforms to improve agility, scalability, and operational efficiency
- Ensure data products are optimized for analytics, predictive modeling, and AI/ML consumption
- Build, mentor, and develop a high-performing teams
- Foster a culture of engineering excellence, ownership, innovation, and continuous improvement
- Promote modern engineering and architectural practices across the organization
- Establish career frameworks, mentorship programs, and capability development strategies for technical teams
- Lead strategic vendor and technology partner relationships supporting data engineering and platform initiatives
Skills
- Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Information Systems, or related field required
- 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 including:
- Snowflake
- Dataiku
- Dbt
- Fivetran
- Apache Iceberg
- Looker / LookML
- Strong technical expertise in:
- Python
- SQL
- ML frameworks and AI tooling
- Cloud platforms such as AWS
- 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
- Master's or PhD preferred
- 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
- 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
Company Overview
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