Director, Data Product Engineering
AVP
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Benefits offered by this job
Job summary
PayNearMe is seeking a Director, Data Products Engineering to lead architecture, engineering, and delivery of AI and data products across our fintech ecosystem. You will drive a product-centric operating model, build scalable data architectures, and enable enterprise data consumption at scale.
The role requires deep expertise in modern cloud data platforms, governance, and cross-functional leadership with a focus on risk, operations, and analytics.
Qualifications
- Bachelor’s degree required; Master’s/PhD preferred.
- 10+ years of leadership in Data/Analytics/AI.
- 5+ years leading enterprise-scale analytics or AI engineering teams.
- Strong hands-on expertise in predictive analytics, ML, and AI-enabled analytics.
- Proven experience building scalable enterprise data products.
- Experience with modern cloud data platforms and analytics ecosystems (Snowflake, Dataiku, dbt, Fivetran, Iceberg, Looker).
- Technical skills in Python, SQL, ML tooling; AWS experience.
- Executive communication and stakeholder management skills.
Responsibilities
- Lead strategic architecture and engineering for domain data solutions and AI/data platform expansion.
- Design scalable, AI-ready data architectures for high-volume workloads.
- Oversee cloud-native data pipelines and data services.
- Partner with Data leadership to enable enterprise data strategies and product-centric operating model.
Skills
Education
Tools
Job description
At PayNearMe, we’re on a mission to make paying and getting paid as simple as possible. We build innovative technology that transforms the way businesses and their customers experience payments. Our industry-leading platform, PayXM™, is the first of its kind—designed to manage the entire payment experience from start to finish. Every click, swipe or tap is seamless, fast and secure, helping non-commerce businesses boost customer satisfaction, accelerate payments, and reduce costs.
Our single platform handles it all: cards, ACH, digital wallets such as PayPal, Venmo, Cash App Pay, Apple Pay and Google Pay, and even cash at more than 62,000 retail locations nationwide. Today, thousands of businesses across consumer lending, iGaming and online sports betting, property management, and tolling trust PayNearMe to deliver a payment experience that drives real results.
In September 2025, we raised a $50 million Series E funding round to accelerate our growth.
We’re a team of 300+ employees across 41 states, headquartered in Silicon Valley with satellite offices in Dallas, TX and Holmdel, NJ.
Join us and be part of a team that’s shaping the future of payments—one experience at a time.
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.
This leader will drive the company’s transition toward a product-centric data operating model by building trusted, reusable, scalable, and business-aligned AI/data products that power analytics, operational intelligence, AI/ML initiatives, customer experiences, regulatory reporting, and enterprise decision-making.
The role requires a strong combination of strategic data solution architecture expertise, modern cloud data engineering leadership, and product-thinking. The ideal candidate will lead teams responsible for engineering high-quality AI/data products, designing scalable data architectures, and enabling reliable enterprise data consumption at scale.
The current ecosystem includes:
About our Stack:
- 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.
- 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.
- 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 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.
- 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.
The annual base salary range for this role represents PayNearMe's good-faith estimate of the base salary it reasonably expects to offer for this position at the time of hire. Actual compensation may vary based on factors including the candidate's experience, qualifications, skills, and work location. PayNearMe may offer compensation outside of this range in certain circumstances. This position will remain posted until filled.
Annual Salary Range
$200,000 — $245,000 USD
- 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
PayNearMe strives to create a workplace where all employees thrive. Our core values represent who we are today and we take pride in the way we work with each other as well as with our stakeholders.
We’re in this together to do the right thing. We deliver real results we are proud of while remaining respectful, transparent, and flexible.
PayNearMe is an equal opportunity employer. We are diligently and thoughtfully working towards cultivating a diverse workforce which in turn, enhances our products and services for the communities we serve. Applicants who represent all backgrounds are strongly encouraged to apply.
Candidate information will be treated in accordance with our job applicant privacy notice found at: https://home.paynearme.com/ccpa-privacy-notice-jobs-employees/
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