Lead Data Warehouse Technical Analyst

Data Warehouse Technical Lead

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

LPL Financial is seeking a highly motivated and experienced Data Warehouse Technical Lead to drive the design, development, modernization, and support of enterprise data warehousing solutions. This role will play a critical part in advancing our cloud-based data platform and analytics capabilities that support Finance, Enterprise Reporting, and Business Intelligence initiatives across the organization.

The ideal candidate is a hands-on data engineering leader with deep expertise in Snowflake, AWS, DBT, SQL, and enterprise data warehousing. This individual will lead technical solution design, mentor team members, and partner closely with business stakeholders while remaining actively involved in data engineering, performance optimization, and production support activities.

Responsibilities:

• Lead the design, development, enhancement, and support of enterprise data warehouse solutions using Snowflake and AWS cloud technologies.
• Build and maintain scalable ETL/ELT pipelines, data integrations, and transformation frameworks supporting Finance, Reporting, and Analytics use cases.
• Develop, optimize, troubleshoot, and review complex SQL queries, data models, and data warehouse structures.
• Drive technical design and implementation of cloud-native data solutions using AWS services including S3, Glue, Lambda, MWAA, and Redshift.
• Partner with business stakeholders, analysts, architects, and engineering teams to translate business requirements into scalable and performant data solutions.
• Establish and promote best practices for data quality, governance, security, monitoring, and operational excellence.
• Support data warehouse modernization, cloud migration, and enterprise data platform initiatives.
• Mentor data engineers and technical analysts while providing technical leadership and guidance across projects.
• Oversee solution deployment, testing, production support, and continuous improvement activities.
• Work in a hybrid work environment in LPL's Austin or Fort Mill offices, effectively partnering with business and technology teams across multiple locations.

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:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field;
  Master's degree preferred.
• Minimum of 10 years of experience in Data Engineering, Data Warehousing, Analytics Engineering, or Data Architecture, or related disciplines.
• Minimum of 5 years of hands-on experience developing and supporting enterprise data warehouse solutions using Snowflake and cloud-based data platforms.
• Advanced SQL development experience, including query optimization, performance tuning, troubleshooting, and data validation.
• Experience designing and implementing scalable ETL/ELT pipelines using AWS cloud technologies and modern data engineering practices.

Core Competencies:

Data Warehousing & Architecture

• Advanced Snowflake development and administration experience.
• Expertise in Enterprise Data Warehouses (EDW), Operational Data Stores (ODS), Data Marts, and dimensional data modeling.
• Strong understanding of data warehouse architecture, performance optimization, and scalability best practices.
• Experience supporting Finance, Enterprise Reporting, Analytics, and Business Intelligence workloads.

Cloud & Data Engineering

• Strong AWS data engineering experience including S3, Glue, MWAA, Lambda, and Redshift.
• Hands-on experience building and supporting cloud-native ETL/ELT pipelines.
• Experience with DBT, Python, and modern data transformation frameworks.
• Expertise in data integration, orchestration, automation, and monitoring.

Data Governance & Quality

• Strong understanding of data governance, data quality, metadata management, and data security principles.
• Experience implementing data validation, reconciliation, and operational controls.
• Ability to ensure accuracy, reliability, and integrity across enterprise data platforms.

Technical Leadership

• Experience serving as a technical lead, senior engineer, or subject matter expert on enterprise data warehouse initiatives.
• Ability to lead technical design discussions and provide mentorship to data engineers and technical analysts.
• Strong communication, stakeholder management, and cross-functional collaboration skills.
• Experience working within Agile delivery…