Senior Data & Analytics Architect

As the Engineering Architecture Lead at Principal Financial Group, you play a crucial role in shaping and advancing the enterprise analytics architecture to ensure its reliability, scalability, and readiness for AI integration. This opportunity allows you to work with cutting-edge cloud-based data systems and contribute significantly to critical decision-making processes within the organization. Key Responsibilities: - Define and maintain enterprise data management and reporting architecture blueprints, vision, principles, and target states. - Ensure alignment with enterprise architecture strategy, business capabilities, and operating models. - Handle, maintain, and enhance the health of data and analytics capabilities for the enterprise. - Develop analytics solutions optimized for BI reporting, self-service analytics, and advanced analytics/AI consumption. - Lead the analytics architecture roadmap in alignment with business priorities. - Act as the build authority for analytics modeling and consumption patterns. Data Modeling & Semantic Layer: - Take ownership of analytical and dimensional data models used in enterprise reporting. - Establish and govern conformed dimensions, business metrics, and benchmarks. - Enable tool-agnostic analytics consumption across multiple BI platforms. - Maintain consistency of definitions across dashboards, reports, and AI use cases. Data Products & Marketplace Enablement: - Promote a data-as-a-product approach for analytical datasets. - Define analytics data products with clear onboarding, versioning, and support processes. - Facilitate discoverability, trust, and reuse through catalog and marketplace integration. Modern Data Platform Architecture (Snowflake): - Architect analytical solutions on Snowflake with a focus on performance optimization and cost efficiency. - Define guidelines for analytical table formats, warehouse and cluster sizing strategies, and query optimization. - Provide guidance to teams on Snowflake SQL, notebooks, and compute patterns. Governance, Quality & Security: - Establish governance focused on analytics for cloud data platforms. - Define and monitor analytics data quality rules. - Ensure compliance with enterprise security, privacy, and regulatory standards. Collaboration & Leadership: - Collaborate closely with data engineers, analytics and BI teams, data scientists, and architects. - Offer architectural leadership and build governance. - Mentor teams on analytics modeling, platform usage, and guidelines. Qualifications: - Over 18 years of experience, including 8+ years in data & analytics architecture or related roles, with a minimum of 3 years hands-on experience in designing on modern cloud data platforms like Databricks or Snowflake. - Hands-on architectural experience with Databricks and/or Snowflake. - Proficiency in quantitative and complex data modeling, SQL, semantic layers, ETL/ELT patterns, and analytics pipeline build. - Experience with AWS cloud platform or equivalent, understanding of business requirements translation, and strong communication and collaboration skills. Location: Pune & Hyderabad Preferred Qualifications: - Experience in BFSI sector is preferable. - Architecture or cloud certifications are a plus. As the Engineering Architecture Lead at Principal Financial Group, you play a crucial role in shaping and advancing the enterprise analytics architecture to ensure its reliability, scalability, and readiness for AI integration. This opportunity allows you to work with cutting-edge cloud-based data systems and contribute significantly to critical decision-making processes within the organization. Key Responsibilities: - Define and maintain enterprise data management and reporting architecture blueprints, vision, principles, and target states. - Ensure alignment with enterprise architecture strategy, business capabilities, and operating models. - Handle, maintain, and enhance the health of data and analytics capabilities for the enterprise. - Develop analytics solutions optimized for BI reporting, self-service analytics, and advanced analytics/AI consumption. - Lead the analytics architecture roadmap in alignment with business priorities. - Act as the build authority for analytics modeling and consumption patterns. Data Modeling & Semantic Layer: - Take ownership of analytical and dimensional data models used in enterprise reporting. - Establish and govern conformed dimensions, business metrics, and benchmarks. - Enable tool-agnostic analytics consumption across multiple BI platforms. - Maintain consistency of definitions across dashboards, reports, and AI use cases. Data Products & Marketplace Enablement: - Promote a data-as-a-product approach for analytical datasets. - Define analytics data products with clear onboarding, versioning, and support processes. - Facilitate discoverability, trust, and reuse through catalog and marketplace integration. **Modern Data Platfor