Principal Azure Data Architect – Insurance Domain

• Design and deliver scalable, secure, and business-aligned solution architectures for insurance platforms and applications.
• Collaborate with business, analytics, and technology stakeholders to translate strategic objectives into end-to-end solution designs.
• Provide architecture leadership across applications, integrations, data platforms, cloud technologies, and digital transformation initiatives.
• Leverage data analytics, quantitative analysis, and business insights to identify opportunities for innovation, operational efficiency, and profitable growth.
• Drive strategy development by aligning technology solutions with business goals, market demands, and customer needs.
• Support digital commerce, underwriting, claims, and policy administration processes through modern technology solutions.
• Create compelling architecture roadmaps and data-driven presentations using strong data storytelling techniques.
• Partner with cross-functional teams to improve sales, marketing, and supply chain-related processes where applicable within the insurance value chain.
• Manage stakeholder expectations and provide architectural governance throughout the project lifecycle.

• Strong insurance domain experience, preferably within the Lloyd’s marketplace.
• Good understanding of tools and platforms used across the Lloyd’s insurance ecosystem.
• Proficiency in Azure ecosystem: Blob Storage, Data Lake, Synapse Analytics, Databricks, Functions, and Monitor.
• Demonstrated expertise in analytics consulting, data analysis, and data analytics.
• Strong business acumen with the ability to connect technology decisions to business outcomes.
• Experience identifying business opportunities and driving innovation through technology and data.
• Proven ability to develop strategies that support business transformation and profitable growth.
• Strong stakeholder management, consulting, and communication skills, including data storytelling and executive presentations.
• Experience with sales analysis, marketing insights, and quantitative analysis is preferred.
• Knowledge of enterprise architecture frameworks, cloud platforms, integration solutions, and modern data ecosystems.

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