Manager, Software Engineering Product Manager (Annuity Data Platform)

About the role

This role will work a hybrid schedule coming into the Columbus, Ohio office 2 days per week on Wednesdays & Thursdays.

Roles and Responsibilities

• Annuity Data Platform Strategy and Roadmap
  • Define and drive the strategic direction for the Annuity Data Platform in alignment with organizational goals, the Annuity Modernization Program, and broader Data Strategy priorities.
  • Establish an outcome-based roadmap for ADP that balances first-launch delivery commitments with longer-term platform scalability, reuse, analytics, and AI enablement.
  • Partner with architecture and business leaders to ensure the platform supports critical modernization capabilities, downstream consumers, and future-state reporting, analytics, and AI needs.
• First-Launch Delivery Execution
  • Lead the ADP team in delivering data capabilities required for Annuity Modernization first launch, including support for priority business capabilities and critical-path features.
  • Ensure backlog readiness, sequencing, and alignment to milestone planning, integrated plans, and cross-team handoffs so the ADP team can execute predictably against committed outcomes.
  • Drive resolution of scope, dependency, and capacity issues impacting delivery, while maintaining focus on business value, schedule commitments, and quality.
• Data Platform Engineering and Operational Excellence
  • Lead the design, development, and operationalization of scalable, secure, and resilient data platform capabilities that meet business and technology needs.
  • Establish and mature engineering practices across the ADP team, including DevSecOps, automation, observability, and support for reliable run operations.
  • Ensure strong controls around platform health, data quality, stability, support readiness, and risk mitigation as ADP becomes foundational to multiple annuity capabilities.
• Data Strategy and AI Enablement
  • Partner with enterprise and program data leaders to shape and implement Data Strategy for Annuity, including data modeling, lineage, governance, and reusable platform patterns.
  • Identify high-value opportunities for AI-based solutions enabled by trusted, governed, and reusable data assets on the ADP platform.
  • Help define and mature foundational AI capabilities in the data space, including reliable data pipelines, governed data assets, reusable data products, and platform patterns that enable analytics, automation, and AI use cases.
  • Ensure the platform enables trusted, consumable data for operational processes, regulatory needs, reporting, analytics, and future AI-driven solutions.
• AI and Business Solution Enablement
  • Work closely with business stakeholders to understand pain points, process inefficiencies, and decisioning opportunities that can be addressed through data and AI-based solutions.
  • Partner across business and technology teams to translate opportunities into actionable use cases, roadmaps, and delivery plans.
  • Promote pragmatic adoption of AI-enabled capabilities that improve operational efficiency, speed to insight, and business value while aligning to enterprise standards and risk controls.
  • Ensure AI and data solutions are tied to measurable business outcomes and support the broader goals of Annuity Modernization.
• Cross-Functional Collaboration
  • Foster close partnerships across Annuity Technology, IDS, Data Architecture, Program Leadership, and business stakeholders to ensure seamless execution of platform and capability delivery.
  • Work closely with partner teams such as ALIP, Real Time Integrations, Workflow, Correspondence, and other impacted assets to manage interdependencies, resolve blockers, and align delivery plans.
  • Serve as a key leadership face-off for ADP within planning, governance, and escalation forums.
• Workforce, Vendor, and Financial Management
  • Develop and manage a workforce strategy for the ADP team that aligns skills and capacity to modernization demand, platform priorities, and first-launch commitments.
  • Manage vendor relationships and external partnerships to ensure high-quality delivery, efficient onboarding, and effective scaling where needed.
  • Optimize build and run costs while maintaining delivery quality, platform resiliency, and long-term value realization.
• Continuous Improvement and Team Leadership
  • Build a strong, engaged engineering culture that emphasizes accountability, collaboration, learning, and continuous improvement.
  • Strengthen the team’s ability to plan, execute, and support data platform work through clear operating rhythms, performance measures, and talent development.
  • Stay current on industry trends in data platforms, cloud, automation, analytics, and AI, and apply those learnings to improve team effectiveness and platform outcomes.

Qualifications

• Proven experience leading software engineering and/or data platform teams in large, complex technology environments.
• Strong understanding of data platforms, data engineering, data architecture, and modern software delivery practices.
• Experience leading transformational programs with significant cross-functional dependency management, delivery execution, and operational accountability.
• Strong knowledge of DevSecOps, SRE/operational practices, automation, and engineering maturity improvement.
• Experience enabling data-driven and AI-supported solutions through strong partnership with business stakeholders, architects, and engineering teams.
• Strong understanding of the foundational capabilities needed to support analytics, automation, and AI use cases, including data quality, governance, lineage, and scalable platform design.
• Excellent collaboration, communication, and stakeholder management skills, with the ability to influence across business and technology organizations.
• Able to lead and inspire cross-functional teams while balancing immediate delivery needs with longer-term strategic platform outcomes.
• Up-to-date knowledge of technology trends and software engineering discipline, particularly in cloud, data, analytics, and emerging AI capabilities.