Senior Vice President, Head of Core Data Technology

Senior Vice President, Head of Core Data Technology

LPL Financial

Help reimagine the data foundation that powers advisor experiences, client reporting, trading, regulatory obligations, and the next generation of AI-enabled services. This executive role offers the opportunity to modernize LPL's core books-and-records capabilities while building an AI-native organization focused on trusted, real-time, agent-ready data.

Job Overview:

The Senior Vice President, Head of Core Data Technology will lead the strategy, architecture, delivery, and operation of LPL's core data platforms, including transactions, positions, tax lots, security master, pricing, investment accounting, sleeve-level accounting, and held-away assets. Reporting to the CIO of Data Technology, this leader will also serve as the technology lead for the Data Quality Center of Excellence and drive the optimization and acceleration of the LPLSQL migration to AWS systems of record. The role will establish AI and generative AI as core capabilities across data engineering, quality, operations, and consumption, with strong controls for accuracy, security, auditability, and regulatory compliance.

Responsibilities:

·   Own the strategy, architecture, and delivery of real-time, event-driven books-and-records platforms for transactions, positions, tax lots, investment accounting, and sleeve-level accounting, with continuous reconciliation and auditable history.

·   Lead AI-driven ingestion, normalization, entity resolution, anomaly detection, and quality controls for LPL-custodied and held-away data, including clear provenance, freshness, completeness, and confidence measures.

·   Modernize security master and pricing capabilities through intelligent instrument enrichment, identifier resolution, valuation controls, vendor-source management, and explainable exception workflows.

·   Build and govern semantic data products, including enterprise ontology, knowledge graphs, searchable metadata, data contracts, lineage, and curated views that support both human users and AI agents.

·   Expose core data through secure, governed APIs and Model Context Protocol services, enforcing entitlement-aware access, PII protection, observability, audit trails, and controls against data exfiltration and prompt-based threats.

·   Establish an AI-native engineering and operating model in which AI coding agents, automated testing, evaluation frameworks, and agentic data operations improve delivery speed and quality while people retain accountability for architecture, judgment, and assurance.

·   Optimize and accelerate the migration of LPLSQL capabilities to AWS systems of record through disciplined target architecture, sequencing, automated conversion, lineage discovery, parity testing, and risk controls.

·   Serve as technology lead for the Data Quality Center of Excellence, establishing enterprise standards for profiling, quality rules, anomaly detection, ownership, remediation, measurement, and transparency.

·   Partner with Compliance, Risk, Legal, Internal Audit, Model Risk Management, Product, Operations, and Data Governance to ensure AI-enabled data capabilities meet broker-dealer, investment adviser, privacy, supervision, client reporting, and cost-basis obligations.

·   Lead and develop a multidisciplinary organization spanning data engineering, AI and machine learning, knowledge engineering, data products, and data quality; attract top talent and build AI fluency across the team.

·   Manage strategic relationships with account aggregators, pricing and reference-data providers, cloud and data-platform partners, and other critical vendors.

What are we looking for?

We're looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.

Requirements:

·   15+ years of technology experience, including senior leadership of enterprise data platforms in wealth management, brokerage, custody, clearing, asset management, or another highly regulated financial-services environment, with direct ownership of books-and-records data.

·   Demonstrated success putting AI, generative AI, machine learning, or agentic capabilities into production at enterprise scale with measurable outcomes, strong evaluation practices, and appropriate controls.

·   5+ years leading multidisciplinary engineering and data teams of more than 20 people, including organizational transformation, talent development, vendor leadership, and executive stakeholder management.

·   Deep expertise across transactions, positions, tax lots and cost basis, corporate actions, security master, pricing, investment accounting, held-away data, and real-time or event-driven data architectures.

·   Bachelor's or master's degree in computer science, data science, engineering, or a related field, or equivalent relevant experience.

Core Competencies:

·   AI-native technology strategy, including agentic architecture, retrieval-augmented generation, context engineering, AI evaluation, observability, and secure production operations.

·   Cloud and data architecture across AWS, Snowflake, streaming and event-driven platforms, relational and NoSQL stores, knowledge graphs, semantic layers, vector search, APIs, and microservices.

·   Executive leadership in regulated environments, with the ability to translate complex technology and data risks into clear decisions, operating models, roadmaps, and measurable outcomes.

·   Data governance, master data management, metadata, lineage, data quality, entitlements, privacy, auditability, and responsible AI controls.

·   Product mindset and strong partnership across Technology, Product, Operations, Risk, Compliance, Legal, Audit, and business leadership.

Preferences:

·   Experience with Amazon Bedrock, Amazon SageMaker, Snowflake Cortex, Kafka, Amazon Kinesis, AWS Lambda, Amazon Neptune or Neo4j, Amazon OpenSearch, or comparable enterprise platforms.

·   Experience designing enterprise ontologies or knowledge models, including familiarity with the Financial Industry Business Ontology (FIBO).

·   Experience with advisor, brokerage, custody, clearing, managed-account, unified managed account, alternative investment, annuity, retirement-plan, or account-aggregation data.

·   Working knowledge of Model Context Protocol, agent-to-agent patterns, AI coding agents, spec-driven delivery, and automated testing for AI-generated code.

·   Experience leading large-scale legacy data-platform modernization or migration to cloud-based systems of record.

Pay Range:

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 have the flexibility to do business their way. And they have the freedom to manage their client relationships, because they know their clients best. Simply put, we take care of our advisors and institutions, so they can take care of their clients.

For further information about LPL, please visit www.lpl.com.

Join the LPL team and help us make a difference by turning life’s aspirations into financial realities. Please log in or create an account to apply to this position. Principals only. EOE.

Information on Interviews:

LPL will only communicate with a job applicant directly from an @lplfinancial.com email address and will never conduct an interview online or in a chatroom forum.  During an interview, LPL will not request any form of payment from the applicant, or information regarding an applicant’s bank or credit card.  Should you have any questions regarding the application process, please contact LPL’s Human Resources Solutions Center at (855) 575-6947.

EAC 5.19.26