VP, Data Intelligence Transformation

Where Ambition Meets Innovation

Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and more, you’ll find the ingredients you need at LPL Financial to shape your success while helping clients pursue their financial goals.

Job Overview:

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.

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.

What Are We Looking For?

We are seeking a strategic and technically accomplished enterprise leader who can connect complex data, analytics, and AI capabilities into a cohesive business outcome. The ideal candidate demonstrates the ability to pursue greatness through transformative thinking, act with integrity when making governance and technology decisions, remain driven to help our clients succeed by enabling trusted and scalable data consumption, win together through cross-functional influence and collaboration, and create and share joy by fostering alignment, simplification, and measurable impact across the organization.

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.

Preferences:

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.

Pay Range:

$163,900.00 - $273,100.00

Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play – such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!

Company Overview:

LPL Financial Holdings Inc. (Nasdaq: LPLA) is among the fastest growing wealth management firms in the U.S. As a leader in the financial advisor-mediated marketplace(6) , LPL supports over 32,000 financial advisors and the wealth management practices of approximately 1,100 financial institutions, servicing and custodying approximately $2.3 trillion in brokerage and advisory assets on behalf of approximately 8 million Americans. The firm provides a wide range of advisor affiliation models, investment solutions, fintech tools and practice management services, ensuring that advisors and institutions have the flexibility to choose the business model, services, and technology resources they need to run thriving businesses. For further information about LPL, please visit www.lpl.com.

At LPL, independence means that advisors and institution leaders have the freedom they deserve to choose the business model, services, and technology resources that allow them to run a thriving business. They h