Technical Solution Leader – Azure Data & Insurance Analytics

100% remote
Either US or Canadian candidates
2 rounds video interview

Job Role: Technical Solution Leader – Azure Data & Insurance Analytics
Location: Canada/USA- Remote
Duration: 6+ Months
No of position: 1
Exp. Start date: 1^st week of May
Year of Experience: 10- 12 Years
Type: Contract


Role Overview
We are looking for a Technical Solution Leader with deep expertise in Azure data platforms and the Insurance domain to drive end-to-end data solutioning. This role requires strong ownership across architecture, data strategy, stakeholder alignment, and delivery of scalable, high-performance data ecosystems that enable business insights and actuarial outcomes.

Key Responsibilities

• Lead the design and implementation of end-to-end data architectures using Azure-native services such as ADLS, ADF, Azure Synapse Analytics, Azure SQL, and Azure Databricks.
• Define and drive data strategy, architecture standards, and best practices across programs.
• Architect and implement scalable data pipelines aligned with medallion architecture (Bronze, Silver, Gold layers).
• Oversee data discovery, profiling, and mapping initiatives across multiple enterprise systems.
• Translate complex business requirements into data models, transformation logic, and scalable solution designs.
• Conduct gap analysis and define target-state data architecture.
• Establish and enforce data governance, data quality frameworks, and validation processes.
• Lead the design of insurance-specific data models supporting underwriting, claims, actuarial, and financial reporting.
• Collaborate with stakeholders to identify optimal source systems and define ingestion strategies.
• Define and implement data ingestion, integration, and orchestration frameworks.
• Drive data reconciliation, validation, and audit mechanisms for accuracy and compliance.
• Lead data migration and modernization initiatives.
• Analyze and optimize pipelines and databases for performance, scalability, and cost efficiency.
• Drive operating model design, governance forums, and cross-functional alignment.
• Ensure delivery of key artifacts including data dictionaries, validation catalogues, architecture documents, and onboarding frameworks.

Required Skills & Experience

• 10–12+ years of experience in data architecture, data engineering, or large-scale transformation programs.
• Strong experience with high-volume insurance datasets (policy, premium, exposure, claims, financials).
• Solid understanding of actuarial processes and insurance KPIs, including:
  • Renewal Ratio
  • Submission to Quote / Quote to Bind
  • Decline Ratio
  • GWP (Gross & Renewal)
  • Loss Ratios (Paid, Incurred, Developed, Projected)
  • Rate Adequacy & Risk-Adjusted Rate Change
  • Probability metrics (by class and exposure group)
  • Rate Indications
• Expertise in:
  • Data architecture and modeling
  • Source-to-target mapping
  • Data definition and metadata management
• Proven ability to define and enforce data governance and data quality frameworks.
• Hands-on experience building insurance domain data models.
• Strong expertise in data ingestion, transformation, and orchestration frameworks.
• Solid understanding of distributed data processing concepts.
• Strong stakeholder management with the ability to engage business, actuarial, and engineering teams.
• Proven track record of delivering scalable, high-performance, and cost-optimized data solutions.

Preferred Skills

• Experience with enterprise data models and data standardization initiatives.
• Prior experience in Insurance (P&C) cloud-based data & analytics programs.
• Hands-on experience with PySpark and Spark-based processing frameworks.
• Strong exposure to Databricks optimization and best practices.
• Strong analytical and problem-solving mindset with a focus on solution architecture and business impact.
• Excellent communication and leadership skills to drive cross-functional collaboration.