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# Senior IT Data Engineer

- **Company:** Mosaic Inc.
- **Location:** Durham, NC, United States
- **Experience:** Expert
- **Salary:** $103,043.0 - $154,563.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Information Engineering, Extract Transform Load (ETL), Data Vault Modeling, Python (Programming Language), Cloud Services, Software Deployment, SQL Databases, Azure Data Factory, Informatica Powercenter, Build Management, Storage Technologies, Enterprise Integration, Software Version Control, Data Pipelines
- **Published:** September 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=2a5af9c4228b37cb

## About the Role

* Bachelor's degree required; 4-6 years of data engineering experience.
 * Advanced SQL proficiency and strong Python skills for data pipeline development.
 * Deep experience with data pipeline tools (e.g., dbt, Azure Data Factory, Airflow, Informatica) and cloud data platforms.
 * Experience with data modeling including dimensional design, data vault, or medallion architecture patterns.
 * Demonstrated ability to manage data engineering projects independently.
 * Professional-level cloud or data engineering certification preferred.

## Description

Designs and develops enterprise data pipelines, data models, and platform integrations that support analytics, clinical, and operational use cases at the organization. Leads data engineering workstreams independently, contributes to platform architecture, and serves as a technical resource on complex data challenges., * Design and build scalable data pipelines, ETL/ELT processes, and data models that serve analytics, clinical, and operational consumers.

 * Lead data engineering workstreams from requirements through production deployment, managing technical quality and delivery milestones.
 * Develop and optimize SQL, Python, and pipeline code to ensure performance, reliability, and maintainability at scale.
 * Contribute to data platform architecture decisions including storage design, processing patterns, and tooling selection.
 * Identify data quality issues and partner with source system owners to drive resolution and preventive improvements.
 * Establish engineering standards for pipeline development, testing, documentation, and version control.
 * Mentor junior data engineers and contribute to capability development across the team.