Azure Data and MLOps Engineer

Chameleon Integrated Services•St. Louis, MO

1d•Remote

About The Position

We are a growing information technology company that offers its employees a culture of success, the chance to work on revolutionary federal IT infrastructure, and the opportunity to grow alongside cutting-edge technology that is reshaping the industry. We are seeking forward-thinking candidates that have strong experience in operational support and can help take to the next level in a proactive stance. Chameleon Integrated Services has expertise in operations management, quality systems, data operations and cybersecurity. We secure some of the most sensitive data for the Department of Defense and for other U.S. federal government agencies. We are known for the great care we take with clients and employees, and we believe in promoting from within.

Requirements

Active Secret clearance.
Hands-on Azure data-engineering experience.
Strong SQL and Python capability.
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 in cloud environments.
Bachelor’s degree in computer science, information systems, engineering, data engineering, or a related discipline; equivalent experience may substitute.
Six or more years in data engineering, cloud engineering, platform engineering, or software integration.
Three or more years using Microsoft Azure.
Experience with at least two major Azure data technologies, such as: Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure SQL, Data Lake Storage, Microsoft Fabric where relevant.
Experience developing REST API, services, databases, 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.
Experience deploying models as endpoints, containers, batch jobs, or integrated services.

Nice To Haves

Azure Government, cARMY, IL4/IL5/IL6, GCC High, or another restricted Government environment.
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.
Experience supporting classified data.

Responsibilities

Build the Azure data pipelines, system integrations, deployment mechanisms, and operational MLOps foundation supporting SEA dashboards, applications, and AI/ML models.
Design SEA data-ingestion and integration architecture.
Connect SEA to additional authoritative Army systems.
Build and maintain pipelines that ingest, transform, reconcile, and synchronize data.
Develop API and service integrations using approved Army patterns.
Support structured, semi-structured, and document-based data.
Implement model-development and deployment environments.
Establish CI/CD, versioning, model packaging, release, rollback, and monitoring.
Configure identity, secrets, logging, alerting, and security controls.
Diagnose data latency, quality, pipeline, model-endpoint, and integration failures.
Produce architecture diagrams, interface descriptions, data-flow diagrams, and operational procedures.
Support Power BI and Power Apps data connections.