Overview
On Site
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Azure Data Lake
Databricks
Azure cloud infrastructure
Hubs
Kafka
Stream Analytics
ARM
Bicep
Terraform
Azure Databricks
Azure Synapse
Python
Spark
SQL
AKS
Docker
BigQuery
Vertex AI
Job Details
We are seeking a Senior Azure Cloud Engineer with deep expertise in building and optimizing cloud-native data platforms, event-driven architecture, and AI/ML workloads. You'll play a key role in shaping our cloud data strategy by designing scalable, secure, and high-performance solutions that drive data intelligence and innovation across the organization.
Responsibilities:
- Design and implement Azure cloud infrastructure to support data engineering pipelines, ML workflows, and AI solutions.
- Architect and operationalize data lake platforms using Azure Data Lake, Databricks, and Delta Lake.
- Build and support real-time and batch data pipelines using services like Event Hubs, Kafka, Stream Analytics, or Azure Data Factory.
- Collaborate with Data Scientists and ML Engineers to enable training, deployment, and scaling of machine learning models.
- Integrate Databricks into enterprise systems for advanced analytics and automation.
- Drive automation, CI/CD, and Infrastructure as Code using Terraform, ARM, or Bicep.
- Ensure performance, cost optimization, and security compliance across the cloud data ecosystem.
- Collaborate cross-functionally to define cloud strategy, evaluate new technologies, and mentor junior engineers.
- Optionally support multi-cloud initiatives, especially in Google Cloud Platform (Google Cloud Platform), to foster portability and resilience.
Requirements:
- 10+ years of experience in cloud engineering with a strong focus on Microsoft Azure.
- Proven experience with Azure Data Lake, Azure Databricks, Azure Synapse, and Data Factory.
- Hands-on expertise in streaming architecture and tools like Kafka, Event Hubs, or Stream Analytics.
- Solid experience with machine learning workflows and AI-enabling infrastructure (e.g., model versioning, inference pipelines).
- Strong proficiency in Python, Spark, SQL, and cloud-native scripting.
- Deep understanding of security, cost governance, monitoring, and resilience in Azure.
- Experience with containerized workloads using AKS or Docker is a plus.
- Familiarity with Google Cloud Platform (Google Cloud Platform) services such as BigQuery, Vertex AI, or Cloud Functions is a bonus.
Preferred Certifications:
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure Data Engineer Associate
- Microsoft Certified: Azure AI Engineer Associate
- Google Cloud Certified (preferred but not required)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.