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 enterpris...

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