Sr Data Warehouse Architect

Description

Summary: The Senior Data Warehouse Architect leads the design, development, and optimization of enterprise data warehouse solutions, focusing on modern cloud data platforms and scalable, performant data solutions. Highlights: 1. Lead design and implementation of enterprise-scale data warehouse solutions 2. Architect and optimize ETL/ELT pipelines using modern tools 3. Provide technical mentorship and establish architectural standards ### **Job Information** Department Name BUSINESS INTEL. \& ANALYTICS Job Type Full time Industry Technology Service Now Ticket INC1472074 Modality WFH Work Experience 5\+ years Assigned Recruiter Contact fernando.bravo.garcia@confie.com Date Opened 03/02/2026 City Tijuana State/Province Baja California Country Mexico Zip/Postal Code 22010 ### **Job Description** 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. 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. 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. 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. 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. 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. ### **Requirements** Experience: * 8\+ years of experience in data warehousing with at least 3 years in architectural roles. * Background in data migration projects and platform modernization initiatives * Familiarity with additional data integration tools and technologies Scholarship: * University/College * Master's Degree Specialized knowledge: * Proven track record of designing and implementing enterprise\-scale data warehouse solutions * Experience in insurance industry with knowledge of policy systems, commission structures, and industry\-specific data challenges Computer knowledge: * Expert\-level SQL skills including advanced optimization techniques, recursive CTEs, window functions, and performance tuning * Deep experience with Snowflake or similar cloud data platforms (Redshift, BigQuery, Databricks) * Experience with BI and analytics tools (Tableau, Sigma, Power BI, or similar) * Strong understanding of data governance, data quality, and metadata management * Experience with Python or other programming languages for data engineering * Knowledge of DataOps practices, CI/CD for data pipelines, and infrastructure as code * Understanding of FinOps principles for cloud data warehouse cost optimization * Experience with customer data platforms, CRM systems, and marketing analytics ### **Benefits** * Private Health Insurance. * Life Insurance. * Saving Funds and Voluntary Savings Account. * Profit Sharing (PTU). * Vacation Days (above law). * Christmas bonus. * Vacation premium.