Technical Solution Leader - Azure Data & Insurance Analytics

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Technical Solution Leader – Azure Data & Insurance Analytics based in the Canada. This role is a senior technical leadership position focused on designing and delivering enterprise-scale data solutions within the insurance domain using Azure cloud technologies. You will own end-to-end solution architecture across data platforms, ensuring the delivery of scalable, high-performance data ecosystems that enable advanced analytics, actuarial modeling, and business intelligence. The role requires deep expertise in Azure-native services, modern data engineering patterns, and insurance data domains such as policy, claims, and financial reporting. You will work closely with business, actuarial, and engineering stakeholders to translate complex requirements into robust data architectures and transformation pipelines. A key aspect of your impact will be defining data strategy, governance frameworks, and architectural standards across programs. This is a highly strategic and hands-on leadership role where your decisions directly shape enterprise data capabilities and analytical outcomes. It is ideal for a professional who thrives at the intersection of architecture, data engineering, and insurance analytics. \n Accountabilities: Lead the design and implementation of end-to-end data architectures using Azure services such as ADLS, ADF, Azure Synapse, Azure SQL, and Azure Databricks. Define and govern enterprise data strategy, architecture standards, and best practices across large-scale insurance data programs. Architect and optimize scalable data pipelines following modern patterns such as medallion architecture (Bronze, Silver, Gold layers). Oversee data discovery, profiling, mapping, and source-to-target transformation across multiple enterprise systems. Translate complex business and actuarial requirements into scalable data models and transformation logic. Establish data governance, data quality frameworks, validation rules, and audit mechanisms to ensure compliance and accuracy. Design insurance-specific data models supporting underwriting, claims, actuarial analysis, and financial reporting. Lead data ingestion, integration, migration, and modernization initiatives across distributed data environments. Drive performance optimization, cost efficiency, and scalability improvements across pipelines and data platforms. Produce key architectural artifacts including data dictionaries, metadata frameworks, and solution documentation. Requirements: 10–12+ years of experience in data architecture, data engineering, or large-scale enterprise data transformation programs. Strong experience working with high-volume insurance datasets including policy, claims, premiums, exposure, and financial data. Deep understanding of insurance and actuarial metrics such as loss ratios, GWP, renewal ratios, submission-to-quote, and rate adequacy indicators. Strong expertise in data modeling, source-to-target mapping, metadata management, and enterprise data architecture design. Proven ability to define and enforce data governance, data quality standards, and validation frameworks. Hands-on experience building scalable insurance domain data models and analytics-ready datasets. Strong knowledge of data ingestion, transformation, orchestration frameworks, and distributed processing concepts. Experience with stakeholder management across business, actuarial, and technical teams in complex environments. Strong analytical mindset with a track record of delivering scalable, high-performance, and cost-optimized data solutions. Experience with Databricks, PySpark, and cloud-based insurance analytics platforms is highly desirable. Benefits: Competitive hourly rate around $70 per hour Fully remote role within the United States or Canada Long-term contract engagement with extension potential Exposure to large-scale insurance analytics and cloud transformation programs Opportunity to work with modern Azure data stack and advanced analytics platforms High-impact leadership role shaping enterprise data strategy and architecture Collaborative environment with cross-functional actuarial, business, and engineering teams Professional growth in advanced cloud data engineering and insurance analytics domains \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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