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# Senior Data Engineer

- **Company:** Chenega Corporation
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $110,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Distributed Computing Environment, Operational Databases, Performance Tuning, SQL Databases, Google Cloud, Azure Data Factory, Data Lakes, Pyspark, Data Management, Data Pipelines, Serverless Computing, Databricks
- **Published:** August 26, 2026
- **Apply:** https://dejobs.org/x/x/1BEA1687E01440079796A57A0F5DF203/job/

## About the Role

* 5+ years of experience with PySpark, SQL, distributed data processing and enterprise-scale data engineering
 * 5+ years of experience designing, developing, owning, and maintaining end-to-end production data pipelines
 * 5+ years of experience with data architecture, including schema design, Medallion architecture, partitioning strategies, and performance optimization.
 * 5+ years of experience collaborating with business stakeholders, gathering requirements, and delivering technical presentations to technical and non-technical audiences
 * 2+ years of hands-on experience with Databricks, including Delta Lake, Unity Catalog, Job orchestration
 * 2+ years of experience with Microsoft Azure, including Azure Data Factory, Azure Functions, Azure Storage, or equivalent cloud platforms such as AWS or Google Cloud Platform (GCP)
 * Experience with Palantir Foundry, including pipeline development, transformation logic, and data modeling
 * Experience supervising others and leading deliverables in cross-functional environments
 * Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
 * Bachelor's degree
 * Successfully pass background and drug screening.

Final salary determination based on skill-set, qualifications, and approved funding.

## Description

Position contingent on contract award - d etails below are subject to change based on final award., * Design, build, and own scalable data pipelines and platform components (Databricks, Palantir Foundry).

 * Engineer robust schemas, medallion patterns, partitioning, and performance tuning (PySpark/SQL).
 * Implement cloudnative orchestration and CI/CD for data services; automate testing/validation.
 * Lead onboarding/migration to data platforms; develop reusable libraries and templates.
 * Champion data quality, observability, and governance; communicate tradeoffs and decisions to stakeholders.
 * Other duties as assigned


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