Role Description We are seeking a Multi-Cloud Architect to design strategies, reference architectures, and platform capabilities that span multiple cloud providers — AWS, Azure, GCP, and selectively OCI, for enterprises operating on more than one cloud by deliberate choice. The role focuses on: - Portability - Abstraction layers - Federated identity - Cross-cloud networking - Platform offerings that hide cloud-specific complexity from product teams The ideal candidate has architected meaningful multi-cloud capabilities, understands the trade-offs between portability and cloud-native depth, and brings strong opinions grounded in production experience. Qualifications - Bachelor’s or Master’s degree in Computer Science or a related field - Eight or more years of experience in cloud architecture roles - Hands-on architecture experience across at least two major cloud providers - Deep understanding of cloud networking, identity, and security across multiple providers - Strong experience with infrastructure-as-code and policy-as-code across clouds - Experience designing federated identity and SSO across cloud platforms - Solid understanding of Kubernetes, container platforms, and managed cloud services - Excellent communication and stakeholder management skills - Multiple cloud certifications across providers - Track record of leading multi-cloud architecture initiatives Requirements - Define multi-cloud strategy, target-state architecture, and adoption guardrails across AWS, Azure, GCP, and OCI as relevant - Design federated identity, SSO, and cross-cloud authorization patterns - Architect cross-cloud networking including transit hubs, private connectivity, and zero-trust patterns - Establish reusable infrastructure-as-code patterns - Define container, Kubernetes, and serverless strategies - Design data architecture strategies for cross-cloud data movement, residency, and analytics - Drive multi-cloud observability, security monitoring, and unified policy enforcement - Establish FinOps practices that operate consistently across multiple cloud providers - Lead disaster recovery and business continuity strategies that span clouds - Partner with security architects on multi-cloud security models, KMS strategies, and key management - Provide guidance to engineering teams on when to use cloud-agnostic versus cloud-native patterns - Produce high-quality architecture artifacts - Engage with cloud providers and partners to evaluate roadmap alignment - Stay current with multi-cloud platform and tooling developments Benefits - Competitive base salary commensurate with experience - Benefits included

• Understand client requirements and lead the creation of robust data platforms leveraging Data Lakehouse architectures, serving as the primary subject matter expert for the Azure data ecosystem (Microsoft Fabric, Azure SQL, and Power BI). • Design and implement scalable data models, ETL/ELT pipelines, and analytics layers using modern cloud ecosystems. • Architect Microsoft Fabric reporting solutions, establishing medallion layering, managing capacity planning, ensuring freshness governance, and configuring CDC/mirroring from Azure SQL into Fabric. • Enforce strict data-layer segregation ensuring PII is excluded by construction, maintaining multi-tenant isolation within the analytics layer, and strictly adhering to 10+ year regulated data retention policies. • Lead complex migration efforts off legacy systems (e.g., AirTable, Smartsheet) to Microsoft Fabric, effectively managing mid-program form and rule drift, and establishing reliable, per-client export channels. • Lead end-to-end analytics projects — from requirement gathering to deployment. • Mentor junior team members, perform code reviews, and ensure adherence to quality standards.**Work closely with cross-functional teams (engineering, product, business) to align data strategy with business goals. • Develop and optimize complex SQL queries, Power BI semantic models, dashboards, and reports (transitioning from legacy LookML/BigQuery paradigms). • Troubleshoot performance bottlenecks, data inconsistencies, and integration challenges. • Stay up to date with advancements in the analytics and cloud data ecosystem. • Drive innovation in reporting and analytics capabilities.**Recommend and implement new tools, frameworks, and practices to enhance the data platform. • Define best practices, coding standards, and governance for analytics projects. • Monitor data systems performance and implement optimization strategies. • Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. • Build and oversee AI-ready data pipelines, focused on feeding scrubbed, segmented data to assistive AI (embeddings, vector stores, and feature stores) and integrating GenAI into analytics and data products. • Drive adoption of AI-assisted data engineering across the team: copilots for SQL/transformation/pipeline code, plus automated testing and documentation. • Define governance and quality standards for data consumed by LLMs and agents.

• Understand client requirements and lead the creation of robust data platforms leveraging Data Lakehouse architectures, serving as the primary subject matter expert for the Azure data ecosystem (Microsoft Fabric, Azure SQL, and Power BI). • Design and implement scalable data models, ETL/ELT pipelines, and analytics layers using modern cloud ecosystems. • Architect Microsoft Fabric reporting solutions, establishing medallion layering, managing capacity planning, ensuring freshness governance, and configuring CDC/mirroring from Azure SQL into Fabric. • Enforce strict data-layer segregation ensuring PII is excluded by construction, maintaining multi-tenant isolation within the analytics layer, and strictly adhering to 10+ year regulated data retention policies. • Lead complex migration efforts off legacy systems (e.g., AirTable, Smartsheet) to Microsoft Fabric, effectively managing mid-program form and rule drift, and establishing reliable, per-client export channels. • Lead end-to-end analytics projects — from requirement gathering to deployment. • Mentor junior team members, perform code reviews, and ensure adherence to quality standards.**Work closely with cross-functional teams (engineering, product, business) to align data strategy with business goals. • Develop and optimize complex SQL queries, Power BI semantic models, dashboards, and reports (transitioning from legacy LookML/BigQuery paradigms). • Troubleshoot performance bottlenecks, data inconsistencies, and integration challenges. • Stay up to date with advancements in the analytics and cloud data ecosystem. • Drive innovation in reporting and analytics capabilities.**Recommend and implement new tools, frameworks, and practices to enhance the data platform. • Define best practices, coding standards, and governance for analytics projects. • Monitor data systems performance and implement optimization strategies. • Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. • Build and oversee AI-ready data pipelines, focused on feeding scrubbed, segmented data to assistive AI (embeddings, vector stores, and feature stores) and integrating GenAI into analytics and data products. • Drive adoption of AI-assisted data engineering across the team: copilots for SQL/transformation/pipeline code, plus automated testing and documentation. • Define governance and quality standards for data consumed by LLMs and agents.

• Understand client requirements and lead the creation of robust data platforms leveraging Data Lakehouse architectures, serving as the primary subject matter expert for the Azure data ecosystem (Microsoft Fabric, Azure SQL, and Power BI). • Design and implement scalable data models, ETL/ELT pipelines, and analytics layers using modern cloud ecosystems. • Architect Microsoft Fabric reporting solutions, establishing medallion layering, managing capacity planning, ensuring freshness governance, and configuring CDC/mirroring from Azure SQL into Fabric. • Enforce strict data-layer segregation ensuring PII is excluded by construction, maintaining multi-tenant isolation within the analytics layer, and strictly adhering to 10+ year regulated data retention policies. • Lead complex migration efforts off legacy systems (e.g., AirTable, Smartsheet) to Microsoft Fabric, effectively managing mid-program form and rule drift, and establishing reliable, per-client export channels. • Lead end-to-end analytics projects — from requirement gathering to deployment. • Mentor junior team members, perform code reviews, and ensure adherence to quality standards. Work closely with cross-functional teams (engineering, product, business) to align data strategy with business goals. • Develop and optimize complex SQL queries, Power BI semantic models, dashboards, and reports (transitioning from legacy LookML/BigQuery paradigms). • Troubleshoot performance bottlenecks, data inconsistencies, and integration challenges. • Stay up to date with advancements in the analytics and cloud data ecosystem. • Drive innovation in reporting and analytics capabilities. Recommend and implement new tools, frameworks, and practices to enhance the data platform. • Define best practices, coding standards, and governance for analytics projects. • Monitor data systems performance and implement optimization strategies. • Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures. • Build and oversee AI-ready data pipelines, focused on feeding scrubbed, segmented data to assistive AI (embeddings, vector stores, and feature stores) and integrating GenAI into analytics and data products. • Drive adoption of AI-assisted data engineering across the team: copilots for SQL/transformation/pipeline code, plus automated testing and documentation. • Define governance and quality standards for data consumed by LLMs and agents.