Director, Data Product Engineering

Responsibilities:

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.

Enterprise Data Product Leadership

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

Strategic Data Solution Architecture

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.

Data Engineering Leadership

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.

Team Leadership & Organizational Development

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.

Minimum 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 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.

Preferred Qualifications

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