Data Engineer, GenAI-Driven Data Platform (Azure/Snowflake)

AssetMark; Charlotte (NC); Hybrid; USD 135,000 - 157,000; Full time

Benefits offered by this job

Flex Time

401K Matching

Medical, Dental, Vision - HSA

Volunteer Time Off

Hybrid Work Schedule

Career Development

Job summary

AssetMark is seeking a Data Engineer (Analytics Engineering) to lead architecture, development, and optimization of data pipelines powering the platform. You will drive reliability and scalability across Azure and Snowflake, integrating GenAI into engineering workflows.

The role requires collaboration with stakeholders, mentoring junior engineers, and delivering governed data assets for analytic consumption from a hybrid Charlotte, NC area office.

Qualifications

• 3–7 years of professional Data/Analytics Engineering experience.
• Snowflake architecture, optimization, and advanced SQL experience.
• Proficiency in SQL/dbt; Python is a plus.
• Strong data modeling skills (Dimensional, Kimball/Inmon).
• Experience with cloud data environments (Azure preferred).
• Familiarity with data observability and governance practices.

Responsibilities

• Lead data architecture and engineering efforts for analytics platforms.
• Design, build, and optimize scalable ELT/ETL pipelines in Snowflake using dbt and SQL.
• Own Azure data infrastructure (Azure Data Factory, Synapse) and data flows to Snowflake.
• Model dimensional data warehouses to support analytics and reporting.
• Champion data quality, observability, and governance across pipelines.
• Mentor junior engineers and drive GenAI integration to accelerate development.

Skills

SQL

dbt

Snowflake

Python

Azure

Data modeling

Data governance

CI/CD

Tools

dbt

Snowflake

Azure Data Factory

Azure Synapse

Airflow

GitHub Actions

Azure DevOps

Job description

AssetMark is seeking a Data Engineer (Analytics Engineering) to lead architecture, development, and optimization of data pipelines powering the platform. You will drive reliability and scalability across Azure and Snowflake, integrating GenAI into engineering workflows.

The role requires collaboration with stakeholders, mentoring junior engineers, and delivering governed data assets for analytic consumption from a hybrid Charlotte, NC area office.