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# Data Engineer

- **Company:** Pantheon Inc
- **Location:** Washington, DC, United States
- **Experience:** Experienced
- **Salary:** $80,000.0 - $120,000.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Word, Microsoft Excel, Amazon Web Services, Microsoft Outlook, Cloud Database, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Meta-Data Management, Microsoft Office, Microsoft PowerPoint, Microsoft SharePoint, Software Engineering, Azure Data Factory, Information Technology, Data Analytics, AWS Data Analytics, Data Pipelines, Api Management
- **Published:** September 24, 2026
- **Apply:** https://www.juju.com/job/16_2f84c3a32

## About the Role

* Bachelor's degree in Data Engineering, Computer Science, Software Engineering, or related field.
 * AWS Data Engineer Associate, AWS Certified Data Analytics, Azure Data Engineer Associate, or equivalent certification.
 * 4 years of data engineering experience, or 3 years with a Master's degree.
 * Ability to work effectively remotely in cross-functional teams.
 * Ability to meet deadlines and produce quality work.
 * Proficient in Microsoft Suite software including Outlook, Word, Excel, SharePoint, and PowerPoint.

Clearance Requirements

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Ability to obtain Public Trust prior to hire and maintain during employment is required.

Work Location: Hybrid - USCG HQ (DHS St. Elizabeth's Campus in D.C.)

 * Hybrid work schedule.
 * Our company prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.
 * If the position is remote or hybrid, you may periodically work from a Pantheon Data office location or client site.
 * If this position is assigned to a Pantheon Data office location or client site, you'll work with colleagues and clients in person, as needed for specific client requirements.

## Description

The Data Engineer develops and maintains enterprise data pipelines, cloud-based data architectures, and automated data integration solutions., * Design and implement ETL/ELT pipelines.

 * Develop cloud-based data solutions.
 * Build API integrations and automated data workflows.
 * Troubleshoot and optimize data pipelines.
 * Support metadata management and data governance initiatives.
 * Collaborate with analysts, data scientists, and stakeholders.


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