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Overview We are seeking a highly skilled Cloud Data Engineer with strong expertise in Microsoft Azure and modern data engineering practices. The ideal candidate will have hands-on experience in cloud-native development, data platform integration, orchestration pipelines, and API development, with a focus on building scalable, secure, and efficient data solutions. Key Responsibilities Design, develop, and optimize cloud-native data solutions on Microsoft Azure . Manage and integrate Azure Entra ID/Azure Active Directory with data platforms for secure access and identity management. Work extensively with Azure Data Lake Storage (ADLS) , including mount point integration in Azure Databricks . Develop and orchestrate data processing workflows using Python and the Apache Spark framework . Administer and tune Databricks clusters , manage Hive Metastore , and leverage Unity Catalog and Medallion Architecture for advanced data governance and architecture. Implement secure secret and key management using Azure Key Vault , integrated with Databricks and Azure DevOps pipelines. Collaborate with cross-functional teams using SCRUM methodology; experience with SAFe framework is a plus. Ingest, monitor, and visualize logs using Azure Log Analytics Workspace . Build and maintain CI/CD pipelines with Azure DevOps and GitHub Actions using YAML. Develop and consume APIs, leveraging Databricks CLI and Azure CLI . Build robust APIs using FastAPI , Pydantic , and deploy via Gunicorn/Uvicorn with Dockerized environments stored in Azure Container Registry (ACR) . Implement distributed messaging and caching solutions using NATS and Redis . Required Skills Cloud & Data Platforms : Microsoft Azure, Azure Databricks, ADLS, Azure Key Vault Programming Languages : SQL, Python, Kusto (KQL), PowerShell, Bash Version Control : GitHub, Azure Repos; strong understanding of branching models, pull requests, and policies Collaboration : SCRUM framework experience Monitoring & Logging : Azure Log Analytics Workspace Automation & CI/CD : Azure DevOps Pipeline, GitHub Actions API Development : FastAPI, Pydantic, REST API design, Docker, ACR Messaging & Caching : NATS, Redis Preferred/Value-Added Skills Experience with Unity Catalog and Medallion Architecture Advanced cluster tuning and optimization in Databricks Data processing with Pandas and Polars Experience with SAFe framework Knowledge of SlowAPI for rate limiting and advanced REST API practices Only shortlisted candidate will be contacted Agensi Pekerjaan Inter Island Sdn Bhd (JTK SM 452C)
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.