Senior Technical Product Manager - Data Lakehouse

Location:
Remote, with a requirement to reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Washington, DC; Dallas, TX; or San Jose, CA.

About the WEX AI Team

At WEX, we are shaping the future of AI-driven financial services and intelligent automation. Our AI team builds foundational systems at the convergence of scalable data infrastructure, machine learning platforms, and real-time decisioning engines. We combine deep technical execution with forward-looking product thinking to transform how data powers business outcomes.

We operate in high-scale, high-complexity environments and collaborate across disciplines-from AI research to cloud engineering-to deliver intelligent, resilient systems that are built to learn and adapt.

About the Role

We are seeking a Senior Technical Product Manager - Data Platform with deep expertise in data-intensive infrastructure, ML-centric data architecture, and cloud-native platforms to drive the development of our next-generation data ecosystem, including AI/ML, data products, and advanced analytics capabilities.

This role will also define and lead efforts to track the performance and value of the data platform-establishing metrics and frameworks to evaluate impact, ROI, and business outcomes of platform investments.

As a senior individual contributor, you will lead product initiatives across our data lakehouse strategy, data pipeline orchestration, and scalable MLOps and other platform integrations-building the foundation for production-grade AI and data applications across the enterprise. You will work closely with cross-functional stakeholders to align platform capabilities with product needs, data strategy, and long-term technical vision.

You will also work with others across the organization to ensure strong data security and privacy practices, governance frameworks, and responsible data stewardship, embedding these principles into platform capabilities and roadmap planning.

How You'll Make an Impact

Data Platform Strategy & Architecture

• Define and execute the product vision for WEXs data platform, supporting lakehouse architecture, broad data product usage, and scalable ingestion of structured and unstructured data.

• Develop phased product roadmaps aligned with evolving AI/ML, analytics, and enterprise data use cases.

• Identify opportunities for innovation in data modeling, metadata management, observability, and compute optimization.

• Drive discovery efforts for infrastructure supporting generative AI, predictive modeling, business intelligence, and decision automation.

• Define and measure platform value and ROI, connecting infrastructure investments with business impact.

Data Infrastructure & Pipeline Optimization

• Lead initiatives to enhance data ingestion, transformation, and delivery across both batch and streaming pipelines-supporting a full spectrum of data use cases.

• Collaborate with engineering to define scalable architecture and orchestration patterns for robust, ML- and analytics-ready data flows.

• Establish requirements for pipeline observability, governance, data freshness, schema evolution, and cost-efficiency.

• Prioritize investments in fault-tolerant and high-throughput compute infrastructure.

AI/ML, Analytics, and Workflow Integration

• Partner with AI, analytics, and MLOps teams to integrate development and deployment workflows into the data platform.

• Define interfaces, APIs, and contracts that streamline access to production data for various use cases.

• Enable faster experimentation through intelligent data caching, feature stores, and monitoring integrations.

• Drive capabilities for reproducibility, traceability, and model lifecycle management.

Cross-Functional Collaboration & Governance Leadership

• Act as the product voice in pods of engineers, data scientists, and cloud architects.

• Align infrastructure and data product initiatives with business KPIs and stakeholder expectations.

• Facilitate alignment across AI/ML, analytics, data governance, and enterprise architecture teams to support a scalable data strategy.

• Promote strong practices for data privacy, compliance, and ethical data use.

Experience You'll Bring

Technical Expertise

• 8 - 10 years in technical product management or engineering roles with a focus on data platforms, large-scale infrastructure, or ML systems.

• Deep understanding of data lakehouse design, cloud-native architecture (AWS, GCP, or Azure), and distributed systems.

• Hands-on familiarity with tools such as Spark, Flink, Kafka, Airflow, DBT, Delta Lake, or equivalent.

• Experience working in environments that integrate ML workflows with streaming/batch data pipelines.

Product Strategy & Delivery

• Proven track record of launching and scaling technical platforms used across engineering, ML, and analytics teams.

• Demonstrated ability to define and measure success metrics tied to system performance, data usability, and AI model outcomes.

• Comfortable working in agile, cross-functional environments with both iterative product development and long-range planning.

Preferred Experience

• Experience with vector databases, retrieval-augmented generation (RAG) pipelines, or generative AI integration.

• Knowledge of data mesh, federated data access, or multi-tenant platform design.

• Background in enterprise-scale financial systems, payments, or regulated data environments.