Data Engineer - AI-Driven Pipelines on Snowflake

National Debt Relief, LLC; United States; On-site; USD 125,000 - 144,000; Full time

Benefits offered by this job

Medical, Dental, and Vision Benefits

401(k) with Company Match

Paid Holidays, Vacation, and Sick Days

Paid Parental Leave

Job summary

National Debt Relief is seeking a Data Engineer to join our Data Engineering team to build, operate, and enhance the data platform that supports analytics and decision-making across the business. You'll work on a Snowflake-based platform, focusing on ingestion, orchestration, transformation, and analytics-ready data models.

The role requires strong SQL and data modeling, experience with modern data stack tools (dbt, Dagster, Snowflake), and the ability to own production outcomes in an AI-enabled

Qualifications

• Strong SQL and data modeling skills with ability to define grain and keys, design incremental strategies, and balance simplicity, performance, and usability.
• Working proficiency across dbt, Dagster, Snowflake; familiarity with Python and infrastructure-as-code; depth in at least one stack area.
• Demonstrated proficiency using AI coding agents with clear context, constraints, task breakdown, and critical review of outputs.

Responsibilities

• Own data engineering projects end to end across ingestion, orchestration, transformation, and analytics layer.
• Develop and maintain Python-based ingestion pipelines when needed, integrating data from APIs and third-party systems.
• Design and build data pipelines and workflows using dbt, Python, Dagster, and Snowflake with sound modeling decisions.

Skills

SQL & data modeling

Education

Bachelor’s degree in a relevant field

Tools

dbt

Dagster

Snowflake

Python

Terraform

Job description

National Debt Relief is seeking a Data Engineer to join our Data Engineering team to build, operate, and enhance the data platform that supports analytics and decision-making across the business. You'll work on a Snowflake-based platform, focusing on ingestion, orchestration, transformation, and analytics-ready data models.

The role requires strong SQL and data modeling, experience with modern data stack tools (dbt, Dagster, Snowflake), and the ability to own production outcomes in an AI-enabled