Azure & Google Cloud Engineer
Akaasa Technologies
New York, NY, United States
about 2 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source
Tech stack
HTML
JavaScript (Programming Language)
.NET Framework
Artificial Intelligence
Microsoft Azure
Bash Shell
BigQuery
C Sharp (Programming Language)
Cascading Style Sheets (CSS)
Cloud Computing
Cloud Database
Cloud Engineering
+40 more
Cloud Storage
Cyber Security
Continuous Integration
Information Engineering
Data Integration
Extract Transform Load (ETL)
DevOps
Disaster Recovery
Domain Name System (DNS)
Github
Identity and Access Management
Virtual Private Networks (VPN)
JQuery
Python (Programming Language)
Network Security
SQL Azure
Performance Tuning
Windows PowerShell
Cloud Services
Azure Machine Learning
Software Engineering
Scripting
Google Cloud
Cloud Platform System
System Availability
Delivery Pipeline
Multi-Cloud
Generative AI
Firewalls (Computer Science)
Containerization
Pyspark
Kubernetes
Infrastructure Automation Frameworks
Information Technology
Bicep
Terraform
Azure Resource Manager
Docker
Key Vault
Databricks
Job description
We are seeking a highly experienced, multi-cloud Azure & Google Cloud Platform (GCP) Engineer to support complex cloud infrastructure, application modernization, and data integration initiatives. The ideal candidate bridges the gap between cloud infrastructure/operations and full-stack software engineering. You will be hands-on in designing, securing, and maintaining cloud-native enterprise solutions while utilizing your software development background to ensure seamless data integration and platform reliability. Key Responsibilities
- Cloud Architecture & Operations: Design, implement, and support scalable cloud solutions across Microsoft Azure and Google Cloud Platform (GCP).
- Infrastructure as Code: Build and maintain cloud environments using IaC tools (Terraform, ARM templates, Bicep).
- CI/CD & Automation: Develop, manage, and optimize deployment pipelines using Azure DevOps, GitHub Actions, or similar tools.
- Security & Networking: Configure cloud networking, DNS, firewalls, VPNs, identity management (IAM), and strict access controls.
- Monitoring & Continuity: Monitor environments, troubleshoot performance bottlenecks, optimize cloud spend, and implement robust disaster recovery/backup strategies.
- Migration Initiatives: Lead and support complex cloud migrations from on-premises legacy environments into Azure and GCP.
- Cross-Functional Collaboration: Partner directly with application development, data engineering, and cybersecurity teams to ensure strict compliance with enterprise governance standards.
- Documentation: Maintain technical architecture diagrams, operational procedures, and stakeholder updates., Senior Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using…
- 1 day ago +
Requirements
- Education: Bachelor’s degree in Computer Science, IT, Engineering, or a related field.
- Experience: 7+ years of dedicated cloud engineering and infrastructure management.
- Azure Mastery: Hands-on experience with App Services, Storage Accounts, Azure SQL, Functions, Key Vault, Azure Machine Learning, and Networking.
- GCP Mastery: Hands-on experience with Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE, and IAM.
- Application Development: 3+ years of professional development experience using C#, .NET, HTML, CSS, and JavaScript/jQuery.
- Data Engineering: Strong expertise in Database management, ETL processes, BI tools, and Python/PySpark programming.
- DevOps & IaC: Fluency in Terraform, ARM/Bicep, and scripting languages (PowerShell, Bash, Python).
Preferred Skills & Certifications (Nice to Haves)
- Certifications: Microsoft Azure (AZ-104, AZ-305, AZ-400) and/or Google Cloud (Associate Cloud Engineer, Professional Cloud Architect, Data Engineer).
- Advanced Data/AI: Experience with Azure Databricks, Vertex AI, and Generative AI platforms.
- Containerization: Experience managing Kubernetes (GKE/AKS), Docker, and enterprise container orchestration.
- Soft Skills: Excellent independent problem-solving, stakeholder communication, and documentation skills in a fast-paced environment.
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