Azure Data Engineer, MLOps

Chameleon Integrated Services

Azure Data and MLOps Engineer building Azure data pipelines and MLOps foundations for the organization. Focused on operational support for SEA dashboards, applications, and AI/ML models.

Posted 7/15/2026contractRemote • Virginia • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining Azure data pipelines, implementing MLOps, and developing API integrations. Proficient in data engineering practices, including ETL/ELT processes, security controls, and operationalizing machine learning models.

Highest-signal resume keywords

Azure Data EngineeringSQL ProgrammingPython ProgrammingETL/ELT Pipeline DevelopmentMLOps Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentAPI IntegrationData TransformationData SynchronizationMachine Learning Model DeploymentData ValidationSchema ManagementError HandlingLoggingRecovery

Tools & Technologies

Azure Data FactoryAzure Synapse AnalyticsAzure DatabricksAzure SQLData Lake StoragePower BIPower AppsGitAzure DevOpsDocker

Certifications & Qualifications

Active Secret ClearanceBachelor’s Degree in Computer Science

Industry Keywords

MLOpsCloud EngineeringDoD System IntegrationData GovernanceData LineageArmy LogisticsAzure GovernmentCARMYIL4/IL5/IL6GCC High

Tech Stack

Tools & technologies

AzureCloudDockerERPETLKubernetesPythonSQLVault

About the role

Key responsibilities & impact

Build the Azure data pipelines, system integrations, deployment mechanisms, and operational MLOps foundation supporting SEA dashboards, applications, and AI/ML models.
Task 4 requires compliant data pipelines, API or service-based integrations, data ingestion, transformation, synchronization, Azure-native services, security controls, integration architecture, data-flow documentation, and validated connections.
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.

Requirements

What you’ll need

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.
Strong preferences 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.

Benefits

Comp & perks

Competitive Employee Health Insurance options including dental
100% company paid vision plan
401K plan with generous company match and no vesting period
100% company paid life insurance
100% company paid long and short-term disability insurance
Training allowance
PTO and more