Lead Data Warehouse Technical Analyst

LPL Financial

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Fort Mill, NCAustin, TX
Salary
$115,600–$192,600 / yr
Posted
8 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $164k
This role $154k
$106k most similar roles pay here $209k

This role pays less than 55% of similar roles. Most pay $129,500–$198,950 — the shaded band above. At the midpoint, this role pays about $154k versus about $164k for comparable roles.

Based on 240 similar postings.

Employer

About LPL Financial

LPL Financial is the largest independent broker-dealer in the United States, providing brokerage and investment advisory services to independent financial advisors and financial institutions. Industry: Financial Services & Wealth Management

LPL Financial currently has 59 open roles on FindRole.

Listed pay typically runs $140,959–$234,882 across 54 roles with salary data.

Most-posted roles

View all roles at LPL Financial

At a glance

TL;DR · Lead Data Warehouse Technical Analyst

Lead Data Warehouse Technical Analyst The Lead Data Warehouse Technical Analyst joins the team to drive the design, development, and modernization of enterprise data warehousing solutions. This role involves building scalable ETL/ELT pipelines, managing data integrations, and developing transformation frameworks to support Finance, Enterprise Reporting, and Business Intelligence initiatives. The individual will perform hands-on data engineering, optimize complex SQL queries, manage data models, and provide technical leadership through mentoring and stakeholder collaboration. Key technologies include Snowflake, AWS services such as S3, Glue, Lambda, MWAA, and Redshift, along with DBT, Python, and SQL. The role focuses on solving challenges related to cloud-native data solutions, performance optimization, and data governance within a large-scale enterprise reporting environment. Essential skills include dimensional modeling, data quality management, and experience with tools like Informatica PowerCenter, Apache Airflow, Terraform, and CI/CD pipelines.

What you'll do

  • Design, develop, and support enterprise data warehouse solutions using Snowflake and AWS cloud technologies.
  • Build and maintain scalable ETL/ELT pipelines and transformation frameworks for finance and analytics use cases.
  • Develop, optimize, and troubleshoot complex SQL queries, data models, and warehouse structures.
  • Implement cloud-native data solutions using AWS services including S3, Glue, Lambda, MWAA, and Redshift.
  • Translate business requirements from stakeholders into scalable and performant technical data solutions.
  • Establish best practices for data quality, governance, security, and operational monitoring.
  • Mentor data engineers and provide technical leadership across various projects and initiatives.
  • Oversee solution deployment, testing, production support, and continuous improvement activities.

What we're looking for

  • Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field; Master's degree preferred.
  • Minimum of 10 years of experience in Data Engineering, Data Warehousing, Analytics Engineering, or Data Architecture.
  • Minimum of 5 years of hands-on experience developing and supporting enterprise data warehouse solutions using Snowflake and cloud platforms.
  • Advanced SQL development skills including query optimization, performance tuning, troubleshooting, and data validation.
  • Experience designing and implementing scalable ETL/ELT pipelines using AWS services such as S3, Glue, Lambda, MWAA, and Redshift.
  • Proficiency with DBT, Python, and modern data transformation frameworks for integration, orchestration, and automation.
  • Proven experience in technical leadership, including mentoring team members and leading design discussions in Agile environments.
  • Preferred certifications include AWS Certification or Snowflake SnowPro Certification.

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