Azure Data & MLOps Engineer

The Azure Data & MLOps Engineer will build the Azure data pipelines, integrations, deployment mechanisms, and MLOps foundation supporting enterprise dashboards, applications, and AI/ML models.

What You’ll Do

• Design data-ingestion and system-integration architecture.
• Connect the analytics environment to authoritative Army systems.
• Build and maintain production pipelines for ingestion, transformation, reconciliation, and synchronization.
• Develop REST API, service, database, file-based, and event-driven integrations.
• Support structured, semi-structured, and document-based data.
• Establish model-development and deployment environments.
• Implement CI/CD, versioning, model packaging, releases, rollback, and monitoring.
• Deploy models as endpoints, containers, batch jobs, or integrated services.
• Configure identity, secrets, logging, monitoring, alerting, and security controls.
• Diagnose data latency, data quality, pipeline, model-endpoint, and integration failures.
• Develop architecture diagrams, interface descriptions, data-flow diagrams, and operational procedures.
• Support Power BI and Power Apps data connections.

• Active final Secret clearance.
• 6+ years of data engineering, cloud engineering, platform engineering, or software integration experience.
• 3+ years using Microsoft Azure.
• Hands-on Azure data-engineering experience.
• Strong SQL and Python skills.
• Experience building production ETL/ELT pipelines and API-based integrations.
• Experience deploying or operationalizing machine-learning models.
• Experience implementing identity, access, secrets, logging, and monitoring within cloud environments.
• Production experience with at least two major Azure data technologies, such as:
• Azure Data Factory
• Azure Synapse Analytics
• Azure Databricks
• Azure SQL
• Azure Data Lake Storage
• Microsoft Fabric
• Experience developing REST API, service, database, file-based, or event-driven integrations.
• Experience with Git, Azure DevOps, or comparable CI/CD tooling.
• Experience with data validation, schema management, error handling, logging, and recovery.
• Bachelor’s degree in computer science, information systems, engineering, data engineering, or related discipline; equivalent experience may substitute.

Strongly Preferred

• Azure Government, cARMY, IL4/IL5/IL6, GCC High, or comparable restricted Government environments.
• Azure Machine Learning, Azure OpenAI, MLflow, Docker, Kubernetes, or model-serving technologies.
• Entra ID, managed identities, Key Vault, RBAC, private endpoints, network controls, and secure secrets management.
• GCSS-Army, SAP, ERP, Army logistics, or DoD system integration.
• Data lineage, metadata, governance, and architecture documentation.
• Power BI gateways, semantic models, or Power Platform integration.
• Classified-data support experience.