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# AI/ML Data Engineer

- **Company:** ALTAMIRA TECHNOLOGIES CORPORATION
- **Location:** Suitland-Silver Hill, MD, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Cloud Computing, Cloud Engineering, Profiling, Code Review, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Digital Assets, Machine Learning, Metadata, Scrum Methodology, Data Streaming, Google Cloud, Data Ingestion, Data Pipelines
- **Published:** November 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7302293280697c3d

## About the Role

* Data Pipeline Development: Build, test, and maintain scalable data ingestion and transformation pipelines. Support ETL/ELT activities to move data from source systems to analytics environments. Ensure data workflows are reliable, monitored, and well-documented., * 10 years of experience with MS/MA degree or equivalent experience
 * Security Clearance: TS/SCI

## Description

Position Description: Data Engineer supports the design, development, and maintenance of data pipelines, data models, and analytics platforms. This entry-level role is ideal for individuals who are beginning their data engineering career and eager to work with modern cloud, ETL, and automation technologies in a collaborative environment., * Data Modeling & Warehousing: Assist in designing and maintaining structured datasets for analytics, reporting, and machine learning use cases.

 * Help define data models, schemas, and metadata within governed data environments.
 * Data Quality & Governance: Perform routine data validation, profiling, and quality checks. Collaborate with senior engineers to implement data governance and security best practices. Contribute to documentation of data flows, lineage, and standards.
 * Cloud & Platform Support: Work with cloud platforms (Azure, AWS, GCP depending on project) to deploy data assets. Support configuration, optimization, and maintenance of compute and storage resources.
 * Collaboration & Delivery: Partner with analysts, data scientists, and product teams to understand data requirements. Participate in Agile ceremonies, sprint planning, and code reviews. Drive continuous learning and contribute to improving engineering processes.