Lead Data Warehouse Technical Analyst

LPL Financial•Charlotte, TX

7d•Hybrid

About The Position

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.

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.
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.
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.
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.
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 environments.

Nice To Haves

Financial Services industry experience preferred.
Experience with PostgreSQL, Oracle, SQL Server, and other enterprise database technologies.
Experience with Informatica PowerCenter and Apache Airflow (MWAA).
Experience with Terraform, GitHub, CI/CD pipelines, and DevOps automation practices.
AWS Certification and/or Snowflake SnowPro Certification preferred.
Experience supporting cloud migration, platform modernization, or M&A integration initiatives.
Experience working within large-scale enterprise reporting and analytics environments.

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.