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# remote Principal Data Engineer

- **Company:** Jobot
- **Location:** United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $205,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Cloud Database, Continuous Integration, Data Mart, Data Structures, Data Vault Modeling, Data Warehousing, Dimensional Modeling, Distributed Data Store, Python (Programming Language), Standard Sql, SQL Databases, Test-Driven Development (TDD), Snowflake, Git Flow, Kubernetes, Information Technology, Data Analytics, Data Management, Data Pipelines
- **Published:** August 15, 2026
- **Apply:** https://www.dice.com/job-detail/2e5d0e60-9f0a-4964-9d3c-bb2999988053

## About the Role

Required:

 * Bachelor's degree in Computer Science, Engineering, or equivalent experience
 * 5+ years of experience building ELT pipelines in a Data Warehouse environment
 * Strong experience with dimensional data modeling (Kimball, Data Vault, Medallion)
 * Hands-on expertise with: dbt, Airflow or Dagster
 * Strong experience with:

o Snowflake or similar cloud data warehouses
o Distributed data systems
o Kubernetes environments

 * Deep understanding of:

o Append-only data modeling & point-in-time data structures
o Column-oriented / analytical SQL modeling

 * Strong proficiency in:

o Python
o SQL

 * Experience implementing:

o Test-driven development (TDD) for data pipelines
o Git-based workflows and CI/CD best practices

Preferred:

 * Experience working within modern data mesh or data platform architecture
 * Exposure to real-time or streaming pipelines
 * Experience supporting large-scale analytics or BI environments

## Description

We are seeking a highly skilled Principal Data Engineer to join our Data & Analytics team. This individual will play a critical role in designing, building, and scaling modern data pipelines and architectures to support enterprise analytics, reporting, and data products.

The ideal candidate has deep expertise in ELT development, dimensional modeling, and modern cloud data platforms, with a strong focus on performance, scalability, and data quality. This is a highly technical, hands-on role with significant ownership across the data lifecycle-from ingestion through curated data marts.


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