Lead Data Warehouse Technical Analyst

Jobtailor

South Carolina

On-site

USD 140,000 - 190,000

Full time

3 days ago

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Job summary

Jobtailor seeks a senior data engineering leader to design and enhance enterprise data warehouse solutions using Snowflake and AWS cloud technologies. You will build scalable ETL/ELT pipelines, optimize complex SQL, and guide data architecture across Finance and BI workloads.

You will mentor engineers, promote data governance, and drive cloud modernization initiatives in a hybrid enterprise setting.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
Minimum of 10 years of experience in Data Engineering, Data Warehousing, Analytics Engineering, 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.
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.
Experience working within Agile delivery environments.
Financial Services industry experience preferred.
Experience with PostgreSQL, Oracle, SQL Server, Informatica PowerCenter, Apache Airflow (MWAA), Terraform, GitHub, CI/CD pipelines, and DevOps automation practices preferred.
AWS Certification and/or Snowflake SnowPro Certification preferred.
Experience supporting cloud migration, platform modernization, or M&A integration initiatives preferred.
Experience working within large-scale enterprise reporting and analytics environments preferred.

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 for 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 S3, Glue, Lambda, MWAA, and Redshift.
Partner with business stakeholders, analysts, architects, and engineering teams to translate business requirements into scalable, 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 and provide technical leadership across projects.
Oversee solution deployment, testing, production support, and continuous improvement activities.

Skills

Data Engineering

Data Warehousing

Analytics Engineering

Data Architecture

SQL Query Optimization

Data Integration

Data Modeling

Cloud Migration

Business Intelligence

Technical Leadership

Mentorship

Agile delivery

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

AWS Certification

Snowflake SnowPro Certification

Tools

Snowflake

AWS S3

AWS Glue

AWS Lambda

AWS MWAA

AWS Redshift

DBT

Python

PostgreSQL

Oracle

Informatica PowerCenter

Apache Airflow/MWAA

Terraform

GitHub

CI/CD

Job description

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 for 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 S3, Glue, Lambda, MWAA, and Redshift
Partner with business stakeholders, analysts, architects, and engineering teams to translate business requirements into scalable, 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 and provide technical leadership across projects
Oversee solution deployment, testing, production support, and continuous improvement activities
Work in a hybrid environment from LPL's Austin or Fort Mill offices while partnering with business and technology teams across multiple locations

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
Minimum of 10 years of experience in Data Engineering, Data Warehousing, Analytics Engineering, 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
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
Experience working within Agile delivery environments
Financial Services industry experience preferred
Experience with PostgreSQL, Oracle, SQL Server, Informatica PowerCenter, Apache Airflow (MWAA), Terraform, GitHub, CI/CD pipelines, and DevOps automation practices preferred
AWS Certification and/or Snowflake SnowPro Certification preferred
Experience supporting cloud migration, platform modernization, or M&A integration initiatives preferred
Experience working within large-scale enterprise reporting and analytics environments preferred

Core Competencies

Demonstrates expertise in designing and implementing enterprise data warehouse solutions using Snowflake and AWS technologies, with a strong focus on ETL/ELT pipeline development, data governance, and performance optimization. Proven ability to lead technical discussions, mentor teams, and drive cloud migration and modernization initiatives.

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