Technical Product Manager - Data

Requirements

• Education and/or experience typically obtained through completion of a bachelor's degree in STEM, Computer Science, Information Systems, Engineering, or related field.
• 5+ years of experience in Product Management, Data Product Management, Platform Product Management, Data Engineering, Analytics Engineering, or related disciplines.
• 3+ years of experience working directly with technical teams such as Data Engineering, Platform Engineering, Software Engineering, Analytics Engineering, or Data Architecture.
• Experience delivering internal platforms, developer tools, data products, or enterprise technology capabilities.
• Strong understanding of modern data platform concepts including data pipelines, data lakes/warehouses, orchestration, metadata, governance, observability, data quality, code management, and application deployment.
• Demonstrated ability to translate complex technical concepts into clear product requirements and

Benefits

Additional Information

At Early Warning, we've powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle®, Paze℠, and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses. Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment. Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship. Overall Purpose The Technical Product Manager is a key role on our Data & AI team charged with defining and delivering the next generation of enterprise data platform capabilities at Early Warning Services. This role is responsible for driving the vision, roadmap, and execution of internal-facing platform products that enable teams across the organization to discover, access, govern, curate, process, deploy, and observe data applications at scale. The primary focus is creating self-service workflows and platform capabilities that improve developer productivity, accelerate delivery, strengthen governance, and enable trusted data consumption across analytics, engineering, product, and business teams. The Technical Product Manager collaborates closely with Data Engineering, Platform Engineering, Analytics, Architecture, Governance, Security, and business stakeholders to translate enterprise needs into scalable platform capabilities, ensuring the data platform is intuitive, reliable, secure, and aligned to business priorities. Essential Functions Execute the product roadmap for enterprise data platform capabilities, including data ingestion, data curation, governance, metadata management, data quality, observability, and self-service data workflows. Partner with Data Engineering, Platform Engineering, Analytics, Architecture, Security, and Governance teams to deliver scalable platform capabilities that support enterprise data needs. Develop a deep understanding of internal platform users-including data engineers, analytics engineers, software engineers, analysts, and data scientists-and translate user needs into platform requirements and product enhancements. Drive the design and adoption of self-service experiences that enable users to onboard data, discover trusted datasets, manage data access, deploy and monitor pipelines, and troubleshoot issues with minimal operational support. Define and prioritize product requirements, user stories, and technical capabilities that improve platform usability, reliability, scalability, and operational efficiency. Establish success metrics and measure platform performance through adoption, user satisfaction, operational efficiency, platform reliability, and business impact outcomes. Partner with engineering teams to define standards, reusable frameworks, and platform patterns that accelerate delivery and promote consistency across data products and pipelines. Ensure data governance, lineage, metadata management, access controls, auditability, and data quality requirements are embedded into platform capabilities and workflows. Collaborate with business and technical stakeholders to identify opportunities for automation, standardization, and process improvements across the data lifecycle. Support the implementation and operationalization of enterprise data capabilities that enable analytics, reporting, operational processes, and data-driven decision making. Balance short-term business priorities with long-term platform investments, technical sustainability, and architectural best practices. Support the company's commitment to risk management by ensuring platform capabilities align with security, compliance, privacy, and enterprise governance requirements while protecting the integrity and confidentiality of systems and data.

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