Lead Data Engineering Manager — Snowflake & AWS

IDR, Inc.; Charlotte (NC); On-site; USD 120,000 - 190,000; Full time

Job summary

IDR, Inc. in Charlotte, NC is seeking a hands-on Data Engineering Manager to lead a small team while modernizing an enterprise data platform. You will mentor engineers, design scalable pipelines using Snowflake, dbt, Python, SQL, and AWS, and balance delivery with leadership.

This role emphasizes hands-on coding and architecture, data governance, and collaboration with stakeholders to deliver trusted analytics and BI outcomes on a modern cloud data stack.

Qualifications

• 6+ years of data engineering experience.
• 4+ years Snowflake, dbt, Python, and AWS experience.
• Experience building data warehouses and data marts.
• Strong SQL and dimensional modeling.
• CI/CD, automated deployments, and data quality testing.
• Mentoring junior engineers while remaining hands-on.
• Familiarity with Airflow, Prefect, or similar.
• Understanding data governance and RBAC.
• Strong communication and collaboration in lean teams.
• Onsite work in Charlotte, NC.

Responsibilities

• Lead and mentor data engineers through code reviews and guidance.
• Build scalable data pipelines and datasets using Snowflake, dbt, Python, SQL, and AWS.
• Translate data needs with stakeholders into reliable solutions.
• Migrate from legacy SQL Server/SSIS to Snowflake.
• Design dimensional data marts for BI and analytics.
• Implement data quality testing, CI/CD, and automated deployments.
• Set engineering standards for data modeling, security, and access.

Skills

Snowflake

dbt

Python

SQL

AWS

Data modeling

CI/CD pipelines

Data governance

Mentoring

Leadership

Airflow

Orchestration

Job description

IDR, Inc. in Charlotte, NC is seeking a hands-on Data Engineering Manager to lead a small team while modernizing an enterprise data platform. You will mentor engineers, design scalable pipelines using Snowflake, dbt, Python, SQL, and AWS, and balance delivery with leadership.

This role emphasizes hands-on coding and architecture, data governance, and collaboration with stakeholders to deliver trusted analytics and BI outcomes on a modern cloud data stack.