Azure Data Architect - Insurance

Role Overview:
You will lead the migration of data and AI architecture to Azure, ensuring robust, scalable, and secure solutions. You will collaborate with business and technical stakeholders to define and implement end-to-end data architectures, from data ingestion to advanced analytics. This role is critical in driving innovation and aligning data strategies with business objectives.

Location: Hybrid/ Dublin (3 Days onsite)
Contract Type: Contract
Duration: 12 months+
Rate: 700-770 per day

Key Responsibilities:

• Design and implement reliable, scalable, and secure data architectures on Azure, focusing on data ingestion, storage, operational consumption, and advanced analytics.

• Migrate on-premise data architectures to Azure PaaS data services, including Azure Data Lake, Databricks, Azure SQL, Azure ML, and PowerBI.

• Develop and maintain MLOps capabilities, ensuring efficient lifecycle management and integration of predictive models.

• Collaborate with IT (DevOps, Security, Infrastructure) and business data teams to align on data architecture solutions and strategy.

• Communicate and validate target architectures with key business and IT stakeholders using templates and frameworks.

• Support the implementation of cloud strategies and enforce compliance with security, governance, and data protection policies (GDPR).

• Lead architecture reviews, assess new technologies, and drive continuous improvement in cost, efficiency, and simplification.

• Engage with third parties for external support and knowledge.

Key Technical Skills:

• Expertise in designing resilient and performant cloud data architectures on Azure, including Data Lake, Lakehouse, and Databricks.

• Hands-on experience with Azure Data Factory, Azure SQL Database, PowerBI, Azure ML, and Cognitive Services.

• Strong understanding of Data Engineering, Data Warehousing, BI/Analytics, Advanced Analytics, and MLOps.

• Proficient in Python, R, SQL, and .NET for analytical programming.

• Knowledge of data governance, security (encryption, authentication, GDPR compliance), and hybrid cloud integration.

• Experience with data modelling (logical & physical) and cross-functional collaboration.

• Familiarity with networking, gateway, and security infrastructure for cloud integration.

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