VP, Data Intelligence Transformation

LPL Financial•Charlotte, NY

About The Position

The VP, Data Intelligence Transformation is a senior individual contributor responsible for defining, building, and operationalizing the enterprise Data Intelligence strategy across LPL Financial's integrated data and AI engineering organization, LENSai. This role serves as the horizontal connector across enterprise data, analytics, AI, and distribution capabilities, establishing the operating model, architecture patterns, governance practices, and technical delivery required to transform governed enterprise data into trusted, reusable intelligence for analytics, reporting, applications, digital products, and AI experiences. The role leads the development and adoption of the Cyan Intelligence Marketplace, enterprise semantic services, context management capabilities, and governed consumption patterns that enable scalable, secure, and observable access to trusted data assets. Working across Enterprise Data Lakehouse (EDLH), Data Warehousing & Automation (DWA), Data Modernization & Sharing (DMS), AI Engineering (AIE), and Data eXperience & Analytics (DXA), this leader drives alignment, integration, and measurable business outcomes while operating without direct ownership of the underlying engineering platforms.

Requirements

15+ years of progressive leadership experience across enterprise data, data platforms, technology strategy, engineering, architecture, product management, or technical delivery functions.
Demonstrated experience defining and implementing enterprise operating models and translating strategy into executable roadmaps, governance frameworks, and measurable outcomes.
Experience across the enterprise data lifecycle, including data platforms, data modeling, data mastering, semantic technologies, metadata management, data products, APIs, event-driven architectures, and modern consumption patterns.
Experience enabling analytics, reporting, digital products, AI, or agent-based solutions through governed enterprise data, business context, and reusable intelligence capabilities.
Experience leading cross-functional initiatives, influencing stakeholders without direct authority, and communicating complex technical concepts to executive audiences.

Nice To Haves

Experience establishing controls for data quality, security, privacy, lineage, resiliency, classification, monitoring, and regulated data usage.
Experience within financial services, wealth management, asset management, or related regulated industries.
Familiarity with advisor, account, position, transaction, security, entity, performance, or related financial data domains.
Experience with AWS, Snowflake, cloud-based data ecosystems, semantic technologies, API and microservices architectures, MCP capabilities, or AI-enabled data platforms.
Experience leading globally distributed engineering, architecture, product, analytics, or data organizations through large-scale transformation initiatives.

Responsibilities

Define and lead the enterprise Data Intelligence operating model, including ownership frameworks, lifecycle practices, governance standards, intake processes, prioritization mechanisms, and delivery models.
Establish and evolve the Cyan Intelligence Marketplace as the enterprise discovery and consumption layer for trusted data products, semantic assets, metadata, context services, APIs, and governed access capabilities.
Lead strategy and technical delivery for enterprise semantic and contextual intelligence services that provide consistent business meaning across analytics, reporting, applications, digital experiences, and AI solutions.
Drive implementation of marketplace capabilities supporting data distribution, API enablement, MCP development, governed MCP access, and additional consumer access channels.
Create an integrated data value lifecycle that connects foundational data platforms, curated assets, semantic services, context management, distribution mechanisms, and consumer-facing experiences.
Partner with AI Engineering and Cyan stakeholders to enable scalable access to authoritative data, business semantics, and contextual intelligence through reusable and governed patterns.
Establish enterprise standards and technical patterns for APIs, events, data sharing, semantic access, and MCP-based consumption, including associated controls, operational expectations, and delivery practices.
Drive consistency across key business domains by partnering with data owners and engineering teams to resolve data definition, lineage, mastering, reference data, and source-of-truth decisions.
Own and manage the cross-LENSai Data Intelligence roadmap, including dependency management, capability sequencing, implementation priorities, and enterprise adoption planning.
Develop performance measures and operating mechanisms that monitor reuse, trust, consumer adoption, time-to-consumption, and business value realization.
Partner with architecture, security, risk, governance, and technology leaders to ensure Data Intelligence capabilities meet security, resiliency, observability, compliance, and regulatory requirements.
Lead executive communications, governance forums, and decision-making processes related to Data Intelligence investments, priorities, tradeoffs, and business outcomes.
Evaluate build-versus-buy decisions and vendor solutions that support semantic, context, metadata, data consumption, integration, and intelligence marketplace objectives.