VP, Business Intelligence Lead

LPL Financial•Fort Mill, SC

4d•$155,300 - $258,800

About The Position

LPL Financial is seeking a senior technology professional to define and execute strategy for enterprise Data Engineering and Data Platform capabilities. This individual contributor role will advance scalable, secure, modern data platforms supporting analytics, business intelligence, artificial intelligence, and data-driven decision making across the enterprise. The work centers on Data Engineering, Data Platform Architecture, and Data Platform Modernization, including cloud-based data ecosystems, platform reliability, governance, and engineering excellence.

Requirements

12+ years of technology experience with enterprise software, data engineering, or platform engineering environments.
Proven experience designing, building, and supporting enterprise Data Engineering and Data Platform solutions.
Experience designing and scaling modern data ecosystems that support enterprise analytics and reporting capabilities.
Experience with enterprise data platforms, data warehouses, data lakes, lakehouse architectures, data mesh frameworks, ETL/ELT pipelines, and data governance programs.
Experience modernizing enterprise data architectures and supporting cloud transformation initiatives.

Nice To Haves

Strong AWS experience and hands-on knowledge of Snowflake, DBT, Terraform, Python, PostgreSQL, CI/CD practices, and Infrastructure as Code (IaC).
Experience improving platform reliability, scalability, governance, and operational maturity.
Experience implementing Data Mesh and Lakehouse strategies at enterprise scale.
Familiarity with AI-assisted engineering tools such as Cursor, GitHub Copilot, or similar technologies.
Experience applying AI capabilities within engineering organizations to improve delivery quality, operational efficiency, and engineering productivity.

Responsibilities

Define and execute strategic initiatives that advance enterprise data platform and data engineering capabilities.
Design and implement scalable data platform architectures for analytics, reporting, AI, and business intelligence workloads.
Lead modernization efforts across cloud data platforms, data warehouses, data lakes, and lakehouse environments.
Establish and advance data mesh capabilities to improve data accessibility, ownership, and scalability across business domains.
Partner with Enterprise Architecture, Security, Infrastructure, Product, and business stakeholders to align technology solutions with organizational priorities.
Improve platform scalability, reliability, governance, security, observability, and operational effectiveness.
Build and evolve enterprise ETL/ELT frameworks and data processing pipelines.
Drive automation, Infrastructure as Code, CI/CD practices, and engineering efficiency improvements.
Evaluate and implement AI-enabled engineering practices and emerging technologies to enhance platform operations and development productivity.