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Responsibilities Design and maintain scalable ETL/ELT pipelines in Azure Databricks to process structured, semi-structured, and unstructured insurance data from diverse sources. Collaborate with architects, modellers, analysts, and stakeholders to deliver tailored data assets for analytics, operations, and regulatory reporting. Develop and optimize batch and streaming data solutions using Azure Data Factory, Data Lake Storage Gen2, Azure Event Hubs, and Kafka. Implement robust data validation, cleansing, and quality controls to ensure reliability for critical insurance use cases. Integrate Informatica tools to support governance, metadata management, lineage tracking, and cataloguing. Enforce data security best practices including RBAC, managed identities, encryption, and compliance with PDPO, GDPR, and other regulations. Automate deployment workflows using GitHub Actions for efficient, repeatable, and auditable data operations. Troubleshoot pipeline issues, conduct root cause analysis, and proactively resolve data quality and performance challenges. Maintain detailed technical documentation for data pipelines, transformation logic, and operational procedures. Apply domain expertise in Hong Kong Life and General Insurance to ensure solutions meet local business and regulatory standards. Requirements Bachelor’s degree in Computer Science, IT, or a related field. 5+ years of experience with Azure cloud platforms, focused on Databricks for insurance data workloads. Strong skills in provisioning and managing Azure Databricks clusters and workspaces for varied data types. Experience integrating Azure Data Factory and Data Lake Storage Gen2 with Databricks for seamless data flows. Proficient in Terraform for infrastructure-as-code deployment of Azure and Databricks services. Hands-on experience with Informatica for metadata management, cataloguing, and governance. Deep understanding of Azure security (RBAC, NSG, Key Vault), monitoring, and cost optimization in regulated environments. Skilled in CI/CD automation using GitHub Actions for platform and pipeline deployments. Proven ability to troubleshoot, optimize, and support mission-critical data workloads in insurance. Strong documentation and communication skills to support cross-functional teams and stakeholders. **This position is offered through a strategic partnership between Don Nelson Technology Limited and NP Solution Limited.
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.