VP, Product Management (Data Lakehouse)

๐Ÿข Dynata ยท all Dynata jobs
๐Ÿ“ United States
๐Ÿ’ฐ USD 250,000 - 300,000 / annual
๐Ÿ“… Posted 2026-08-22 ยท via Himalayas
๐Ÿท VP-Product-Management,Data-Platform-Product-Management,Product-Management,Executive-Product-Management,Data-Lakehouse,Product-Management-VP,VP-Of-Product-Management,VP-Product
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Dynata is seeking a Vice Presidentof Data Platform Products to lead the strategy, development, and adoption of Dynata 'snext-generation data platform andlakehouseecosystem.This leader will define and execute the product vision for Dynata 'sdata platform, ensuring the underlying architecture, governance, and capabilities enable high-value business outcomes across the organization.

Reporting to theChief Product Officer, theSeniorVice President will establish the roadmap for a scalable, governed, and reusable data platform that supports both internal and external use cases.The portfolio includes lakehouse capabilities, federated data access, pricing and feasibility services, semantic-baseddata products, feature management, graph-enabled assets, and externallyaccessibleAI-ready datasets.

Initially, this role will operate as a hands-on product leader responsible for platform strategy, use case prioritization, implementation oversight, and stakeholder alignment. As the platform matures, this leader will build and scale a team to support continued growth and innovation.

Key Responsibilities

Platform Strategy & Product Leadership

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Define and execute the vision, strategy, and roadmap for Dynata 'senterprise data platform andlakehouseecosystem.

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Ensure platform investments are aligned to business priorities and deliver measurable value across analytics, operations, AI, and data product initiatives.

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Identifyopportunities toconsolidateoverlapping data assets, services, and workflows, driving greater reuse, consistency, and platform efficiency across the organization.

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Establish platform investment priorities, business cases, success metrics, and adoption goals to maximize enterprise impact.

Platform Delivery & Adoption

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Lead the product strategy and implementation of Dynata 'slakehouseplatform, partnering closely with engineering, architecture, data science, and vendor teams.

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Translate business and product requirements into platform capabilities that support current and future use cases.

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Partner with business stakeholders to ensure platform-enabled capabilities are adopted, trusted, and embedded into operational and commercial decision-making.

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Continuously evaluate platform performance andidentifyopportunities for optimization, expansion, and innovation.

Use Case Development & Prioritization

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Define and prioritize business use cases enabled by the platform, including feasibility prediction, dynamic pricing, router optimization, graph analytics, syndicated data products, synthetic data products, AI-ready datasets, and advanced analytics.

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Ensure platform capabilities are designed to support reusable, scalable, and governed data products.

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Balance near-term business needs with long-term platform strategy and architectural sustainability.

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Partner with business stakeholders to continuouslyidentifyandvalidatenew platform-enabled opportunities.

Cross-Functional Leadership

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Partner closely with Product,Panel,Technology, Research & Data Science, and Commercial leaders.

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Align stakeholders around investment priorities, platform roadmap decisions, operating models, and adoption strategies.

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Lead cross-functional teams to translate business requirements into scalable platform capabilities, balancing customer needs, technical feasibility, governance requirements, and business impact.

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Build and scale a team of product managers as the data platform portfolio grows.

Qualifications

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10+ years of experience in product management, platform products, data platforms, data infrastructure, analytics, or related fields.

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Proven experience leading large-scale data platform,lakehouse, data warehouse, data mesh, or data infrastructure initiatives.

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Strong understanding of modern data architectures and technologies, includinglakehouse, metadata, governance, semantic layers,ontologies, featurestores, APIs, and platforms such as Snowflake,theApacheecosystem,Iceberg, Spark, Kafka, and Ai

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