The Senior Data Warehouse Architect will lead the design, development, and optimization of enterprise data warehouse solutions that support critical business intelligence and analytics needs. This role requires deep technical expertise in modern cloud data platforms and the ability to architect scalable, performant data solutions that serve diverse analytical requirements across the organization. The ideal candidate will combine technical excellence with strong collaboration skills and a commitment to delivering high-quality, reliable data solutions.
Job Responsibilities
Data Warehouse Architecture: Design and implement dimensional models, data vault structures, and other architectural patterns optimized for analytical workloads. Define data integration patterns, data flow architectures, and transformation strategies that balance performance, maintainability, and flexibility. Lead the architectural evolution of the enterprise data warehouse on Snowflake.
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ETL/ELT Development and Optimization: Architect and optimize ETL/ELT pipelines using modern tools like Coalesce and Wherescape. Design efficient data transformation logic including complex recursive CTEs, hierarchical data structures, and performance-critical queries. Establish patterns for handling slowly changing dimensions, data historization, and temporal data.
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Performance Optimization: Analyze and optimize query performance, implement appropriate clustering strategies, and design efficient data structures. Monitor warehouse performance metrics and implement solutions for query optimization, resource management, and cost efficiency. Establish best practices for performance tuning across the analytics stack
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Data Integration: Lead integration efforts across source systems including policy management systems (Atlas, AMS360), CRM platforms, quoting applications, call center systems, and financial systems. Design robust data pipelines that handle various data formats, frequencies, and quality challenges. Architect solutions for real-time and batch data integration needs.
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Platform Migration Leadership: Lead technical aspects of platform migrations and modernization initiatives. Develop migration strategies that minimize business disruption while improving capabilities. Conduct proof-of-value assessments for new technologies and platforms.
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Technical Leadership: Provide technical mentorship to data engineers and analysts. Establish architectural standards, design patterns, and best practices for the BI&A team. Conduct design reviews and provide technical guidance on complex data challenges. Collaborate with stakeholders across Retail Operations and Supporting Operations Departments to understand analytical requirements and translate them into technical solutions
