Azure & Google Cloud Engineer

Akaasa Technologies

New York, NY, United States

1 day 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

www.careerjet.com

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…
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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.