Director, Data Product Manager - IT Data, Reporting & Analytics

Infoblox•Tacoma, WA

2d•$159,000 - $244,860•Remote

About The Position

Infoblox is seeking a Director, Data Product Manager to join their IT Data, Reporting & Analytics team in the US. This role reports to the Senior Director - Data, Analytics and Reporting. The Director will lead the strategy, roadmap, and execution of Infoblox’s enterprise data products and platforms, aiming to evolve data capabilities from reactive reporting to proactive, AI-enhanced decision intelligence. A key responsibility will be to directly manage and grow a team of Data Product Managers, providing coaching, career development, and operational leadership. The role involves close collaboration with Finance, Sales Operations, Customer Success, Product, IT, and Security to guide high-impact cross-functional initiatives, shape data governance and consumption, and build an operating model for scalable analytics, automation, and AI-driven insights.

Requirements

15+ years of experience in product management, program management, or a hybrid role, with significant time in data, analytics, or infrastructure/platform domains including at least 3-5 years managing product management teams or cross-functional data programs with direct reports.
Proven track record defining and executing strategy and roadmaps for data platforms, analytics products, or decision-support solutions in complex, cross-functional environments.
Direct people management experience — demonstrated track record of hiring, developing, and performance-managing product managers or equivalent roles, ideally in a data or platform context.
Demonstrated ability to operate at multiple altitudes — from portfolio-level prioritization and OKRs to day-to-day project execution and issue resolution.
Strong stakeholder management and executive-level communication skills, with the ability to influence without authority and align diverse technical and non-technical partners.
Experience partnering with data engineering, analytics, and architecture teams; familiarity with modern data stack concepts and tools (e.g., Snowflake, dbt or similar frameworks, BI tools, and cataloging/governance platforms).
Hands-on experience or strong familiarity with applying AI/ML to analytics and data products (e.g., predictive models, recommendations, anomaly detection, or generative AI copilots for discovery, documentation, or reporting).
Demonstrated success designing and implementing intake, prioritization, and delivery operating models for data or platform teams, including governance and portfolio management.
High comfort with ambiguity and early-stage maturity; history of building structure, processes, and standards where few existed and scaling them as organizations grow.
Excellent written and verbal communication skills, including crafting crisp narratives, clear requirements, effective workshops, and senior-level presentations.
Bachelor’s degree in Computer Science, Information Systems, Engineering, Business, or a related field; advanced degree (e.g., MS, MBA) is a plus or equivalent practical experience.

Nice To Haves

Advanced degree (e.g., MS, MBA) or equivalent practical experience.

Responsibilities

Define and own the multi-year vision, strategy, and roadmap for enterprise data products, including core datasets, semantic layers, reporting, analytics, and AI-powered decision support tools.
Build and maintain an outcome-driven data product portfolio that balances foundational platform investments, AI and automation opportunities, and business-critical requests.
Partner with senior business and technology leaders to identify, prioritize, and refine high-value data use cases across revenue, customer, efficiency, and risk domains.
Translate business goals into clear data product requirements, including data sourcing, quality, modeling, access patterns, SLAs, and success metrics.
Lead cross-functional programs from inception through launch, managing scope, dependencies, risks, and communications across IT, data engineering, analytics, architecture, and business teams.
Hire, manage, and develop a team of Data Product Managers, including goal-setting, performance management, and career pathing.
Delegate and distribute work across the data product management team, ensuring appropriate scope ownership at each level while maintaining visibility and accountability.
Coach your team on product thinking, stakeholder management, and delivery execution, actively raising the capability floor of the team over time.
Model and reinforce strong product management practices across the team, including road mapping, requirements clarity, and outcome measurement.
Establish and improve intake, triage, and prioritization processes for data and analytics work, ensuring transparency and alignment on trade-offs.
Define and track KPIs for data products (adoption, reliability, data quality, business impact) and use them to drive continuous improvement and deprecate low-value assets.
Partner with data engineering and platform teams to design scalable, governed data models and pipelines using the modern data stack (e.g., Snowflake, dbt, orchestration, cataloging, BI tools).
Collaborate with data governance and security stakeholders to advance policies for data quality, lineage, access controls, and responsible AI use.
Leverage AI and machine learning (including generative AI assistants and ML-driven analytics) to enhance data discovery, reporting, anomaly detection, and self-service insights.