VP, Data Intelligence Transformation

LPL Financial

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Fort Mill, NCCharlotte, NCNew York, NY
Salary
$163,900–$273,100 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $202k
This role $218k
$142k most similar roles pay here $287k

This role pays more than 66% of similar roles. Most pay $168,687–$235,750 — the shaded band above. At the midpoint, this role pays about $218k versus about $202k for comparable roles.

Based on 240 similar postings.

Employer

About LPL Financial

LPL Financial is the largest independent broker-dealer in the United States, providing brokerage and investment advisory services to independent financial advisors and financial institutions. Industry: Financial Services & Wealth Management

LPL Financial currently has 56 open roles on FindRole.

Listed pay typically runs $131,793–$219,604 across 52 roles with salary data.

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View all roles at LPL Financial

At a glance

TL;DR · VP, Data Intelligence Transformation

VP, Data Intelligence Transformation is a senior individual contributor role within the LENSai organization. This position serves as a horizontal connector across enterprise data, analytics, AI, and distribution capabilities to transform governed data into trusted, reusable intelligence for reporting, applications, and AI experiences. The successful candidate will define the operating model, architecture patterns, and governance practices while leading the development of the Cyan Intelligence Marketplace and semantic services. Key responsibilities include managing the Data Intelligence roadmap, establishing API standards, and ensuring data quality and lineage across various business domains. Required expertise includes experience with AWS, Snowflake, cloud-based data ecosystems, and microservices architectures. The role addresses the challenge of providing scalable, secure access to authoritative data assets while navigating complex requirements for security, resiliency, and compliance within a regulated financial services environment.

What you'll do

  • Define and lead the enterprise Data Intelligence operating model including governance standards and delivery models.
  • Establish and evolve the Cyan Intelligence Marketplace as a discovery layer for trusted data products and metadata.
  • Deliver technical strategies for semantic and contextual intelligence services across analytics, reporting, and AI solutions.
  • Create an integrated data value lifecycle connecting foundational platforms to consumer-facing experiences.
  • Establish enterprise standards and technical patterns for APIs, events, and governed data sharing.
  • Manage the cross-LENSai Data Intelligence roadmap including dependency management and implementation priorities.
  • Develop performance measures to monitor data reuse, trust, and business value realization.
  • Lead executive communications and decision-making processes regarding Data Intelligence investments and trade-offs.

What we're looking for

  • 15+ years of progressive leadership experience in enterprise data, technology strategy, engineering, architecture, or product management.
  • Experience defining and implementing enterprise operating models, governance frameworks, and executable roadmaps.
  • Expertise across the data lifecycle including modeling, mastering, semantic technologies, metadata management, and API architectures.
  • Experience enabling analytics, reporting, digital products, and AI solutions through governed data and reusable intelligence.
  • Proven ability to lead cross-functional initiatives and communicate complex technical concepts to executive audiences.
  • Experience establishing controls for data quality, security, privacy, lineage, and regulated data usage (preferred).
  • Experience in financial services, wealth management, or other regulated industries (preferred).
  • Familiarity with AWS, Snowflake, cloud ecosystems, and AI-enabled data platforms (preferred).

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