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Role Description

The Senior Technical Product Manager (Data Platform) owns the strategy, roadmap, and execution of Zip’s foundational data platform. This is a platform-focused role, not a business use-case PM position. You will be responsible for building and scaling reliable, compliant, and AI-ready data infrastructure that powers analytics, risk modeling, fraud detection, regulatory reporting, and production AI capabilities across the company. This role ensures our data assets are trusted, governed, scalable, cost-efficient, and accessible through self-serve capabilities—while meeting the regulatory standards required in fintech.

You will partner closely with:

• Data Engineering
• ML Engineering
• Agentic AI
• Enterprise Architecture
• Risk
• Compliance
• Product teams

Interesting problems you’ll get to solve:

• Data Platform Strategy & Roadmap:
  • Define and execute the multi-year vision and roadmap for Zip’s enterprise Data Platform.
  • Own foundational capabilities, including ingestion, storage, transformation (ETL/ELT), orchestration, metadata management, and access control.
  • Ensure alignment with company-wide analytics, AI, and regulatory priorities.
  • Balance speed, reliability, scalability, compliance, and cost in roadmap decisions.
• Data Governance, Controls & Compliance:
  • Establish and enforce enterprise data governance frameworks.
  • Implement and maintain SOX-compliant controls across critical datasets and reporting workflows.
  • Define and operationalize data contracts between producers and consumers.
  • Ensure lineage tracking, auditability, and regulatory reporting integrity.
  • Partner with Risk and Compliance to align with data privacy and regulatory requirements (e.g., SOX, KYC, AML, GDPR where applicable).
• Reliability, Quality & Platform Health:
  • Define data quality standards, SLAs, freshness requirements, and certification processes.
  • Establish measurable platform health metrics (uptime, quality scores, adoption, cost efficiency).
  • Drive proactive monitoring and observability for pipelines and datasets.
  • Reduce friction for AI and analytics teams by improving data discoverability and trust.
• AI & Advanced Analytics Enablement:
  • Ensure the data platform supports production-grade AI/ML workloads.
  • Enable reusable, well-governed data foundations for feature engineering and experimentation.
  • Partner with ML Engineering to ensure model-ready, high-quality datasets.
  • Transition the organization from AI experimentation to scalable, production-ready AI capabilities.
• Self-Service & Adoption:
  • Enable self-service analytics capabilities while maintaining governance guardrails.
  • Improve discoverability and usability of certified datasets.
  • Drive adoption of standardized, governed data assets across teams.
• Cost Optimization & Scalability:
  • Partner with engineering to optimize warehouse, compute, and storage costs.
  • Drive architectural decisions that scale efficiently as data volume and AI usage grow.
  • Continuously evaluate tradeoffs between performance, reliability, and cost.

Qualifications

• 7–10+ years in Product Management or equivalent experience, with a focus on data platforms, data engineering, or analytics infrastructure.
• Strong understanding of modern data architectures (lakehouse, warehouse, ELT/ETL, streaming/event-driven systems).
• Experience defining and managing data contracts, governance frameworks, and quality standards.
• Experience operating in regulated environments (SOX compliance strongly preferred; fintech or financial services experience a plus).
• Deep familiarity with data platforms such as Snowflake, BigQuery, Redshift, Kafka/Kinesis, or similar ecosystems.
• Strong ability to translate complex technical capabilities into measurable business impact.
• Demonstrated experience driving cross-functional alignment across engineering, compliance, and business teams.
• Comfortable making principled tradeoffs between speed, reliability, compliance, and cost.

Requirements

• Experience enabling AI/ML workloads through reusable, governed data infrastructure.
• Systems thinker who understands interconnected platform tradeoffs.
• Strong technical fluency with data engineering patterns and architecture decisions.
• Proven ability to drive clarity in ambiguous, evolving environments.
• Experience optimizing infrastructure cost and operational efficiency at scale.
• Ability to influence without authority and lead through alignment.

Benefits

• Flexible working culture.
• Incentive programs.
• Unlimited PTO.
• Generous paid parental leave.
• Leading family support policies.
• Company-sponsored 401k match.
• Learning and wellness subscription stipend.
• Beautiful Union Square office with a casual dress code.
• Industry-leading, employer-sponsored insurance for you and your dependents, with several 100% Zip-covered choices available.