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Solutions Delivery Manager - Semantic Enterprise Data & AI Enablement Lead -Hybrid Webster or Boston

Mapfre · Boston, MA · 1 mo ago
$121k–$182k/yrFull-time

Summary

Mapfre is seeking a Solution Delivery Manager to lead the development and adoption of the enterprise Context Layer, a foundational element that enhances data understanding, trust, and AI capabilities.

About the role

This role is pivotal in establishing a consistent understanding of business concepts across analytics, reporting, data products, and AI solutions, driving innovation and shaping the future of data, knowledge, analytics, and AI integration within the enterprise.

Responsibilities

  • Lead the development, implementation, and evolution of Mapfre's enterprise Context Layer, including ontology, taxonomy, business glossary, metadata, lineage, knowledge graphs, and enterprise semantic models.

  • Define and maintain the semantic framework that enables a consistent understanding of business concepts across analytics, reporting, data products, and AI solutions.

  • Translate business concepts, rules, relationships, metrics, and policies into governed, reusable semantic assets.

  • Enable business users and AI systems to discover, understand, and consume trusted enterprise knowledge.

  • Drive metadata management, business glossary, data quality, certification, and data product governance initiatives.

  • Ensure business context, ownership, governance standards, and trusted definitions are embedded within enterprise data products and analytical assets.

  • Help establish Mapfre's AI-ready data foundation by creating trusted business context for copilots, AI assistants, semantic search, and future agentic AI solutions.

  • Support the development of semantic capabilities that improve AI effectiveness, discoverability, and trust.

  • Partner with Data Engineering, Data Architecture, Analytics, Governance, and AI teams to embed semantic definitions, governance standards, lineage, and data quality requirements into enterprise platforms and solutions.

  • Collaborate with business leaders and Data Owners to establish and maintain a common enterprise language and shared understanding of key business concepts.

  • Lead the resolution of semantic, metadata, and data quality challenges through effective stakeholder alignment and collaboration.

  • Manage delivery roadmaps, priorities, dependencies, and vendor relationships supporting semantic, metadata, governance, and knowledge management initiatives.

  • Drive awareness, adoption, and change management efforts that increase usage of enterprise semantic capabilities across analytics, self-service, data products, and AI solutions.

  • Evaluate emerging semantic technologies, metadata management capabilities, and AI enablement approaches to continuously enhance Mapfre's enterprise knowledge ecosystem and Data & AI strategy.

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Mathematics, Statistics, Data Science, Data Management, Analytics, or a related field.

  • 8+ years of experience in Data Governance, Data Management, Data Architecture, Analytics, or related disciplines.

  • Strong communication, facilitation, stakeholder management, and cross-functional leadership skills.

  • Experience with modern data platforms such as Snowflake, Databricks, Azure, or AWS, and a strong understanding of data architecture and analytics ecosystems.

  • Strong understanding of metadata management, business glossaries, data lineage, governance frameworks, semantic modeling, and data discoverability.

  • Proven ability to work with business stakeholders to define business rules, metrics, standards, and reusable business knowledge.

  • Experience partnering with Data Engineering, Data Architecture, Analytics, or AI teams to design and implement enterprise data solutions.

  • Property & Casualty insurance industry knowledge.

Preferred

  • Experience with enterprise semantic layers, semantic technologies, business semantic modeling, or knowledge management platforms.

  • Experience with metadata management tools such as Atlan, Collibra, or Alation.

  • Hands-on experience supporting AI, GenAI, RAG, Copilot, Agentic AI, knowledge management, or AI enablement initiatives.

  • Experience implementing enterprise-scale Data Governance, Data Product, Metadata Management, or Semantic Layer programs.

  • Experience creating reusable business context, semantic models, and knowledge assets that support analytics, self-service data consumption, automation, and AI solutions.

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