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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Analytics Engineer - **Company:** Crisis Prevention Institute - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Business Analytics Applications, Data Analysis, Application Release Automation, User Authentication, Bioinformatics, Cloud Engineering, Cyber Security, Computer Networks, Continuous Integration, Information Engineering, Data Infrastructure, Data Security, Data Sharing, Dataspaces, Disaster Recovery, Information Lifecycle Management, Key Management, Metadata, Operational Databases, Performance Tuning, Power BI, Cloud Services, SQL Databases, Unstructured Data, Enterprise Data Management, Privacy Controls, Data Server Interface, Snowflake, Data Layers, Infrastructure Automation Frameworks, Data Management, Model Context Protocol, Software Version Control - **Published:** November 3, 2026 - **Apply:** https://www.builtincolorado.com/job/principal-analytics-engineer/12022811?handler=ApplyRedirect ## About the Role * Bachelor's Degree * At least 10 years of progressive experience in data engineering, analytics engineering, data platform engineering, cloud data architecture, or a closely related field, including ownership of business-critical production data platforms. * Extensive hands-on experience architecting, administering, securing, optimizing, and operating Snowflake in an enterprise environment. * Demonstrated experience designing and owning production ingestion, transformation, orchestration, observability, and data-serving patterns across a modern cloud data stack. * Demonstrated success serving as a senior technical authority, reviewing architecture, influencing cross-functional decisions, mentoring experienced engineers, and leading resolution of complex platform issues. * Experience partnering with security, infrastructure, application, analytics, AI, and business teams to deliver secure, governed, highly adopted enterprise data capabilities. * Expert-level Snowflake knowledge spanning architecture, administration, virtual warehouses, workload management, performance tuning, cost governance, data sharing, replication, recovery, security, monitoring, and operational support. * Expert SQL and deep knowledge of data modeling, ingestion, transformation, orchestration, testing, observability, version control, release automation, and production engineering practices. * Deep understanding of enterprise security and governance patterns, including least-privilege access, role design, authentication, network controls, encryption, secrets management, auditing, privacy, lineage, and data lifecycle management. * Strong knowledge of AI-enablement patterns for enterprise data, including secure MCP configuration, governed data access, retrieval and tool-integration patterns, and controls for AI-assisted applications and agents. * Exceptional architecture judgment and the ability to evaluate tradeoffs across simplicity, scalability, security, performance, cost, governance, resilience, and maintainability. * Ability to lead through technical influence, conduct rigorous design and code reviews, mentor experienced practitioners, establish standards, and build alignment across teams without relying on formal authority. * Strong communication, consulting, and stakeholder-management skills, with the ability to explain complex platform decisions to technical and executive audiences and connect engineering choices to business outcomes. * Demonstrated ownership, sound judgment, intellectual curiosity, and the ability to operate independently across high-impact priorities while partnering closely across the data team and enterprise. We'd Love to See: * Deep experience with Snowflake-native capabilities, ingestion technologies such as Fivetran, cloud services, CI/CD, infrastructure automation, and enterprise business intelligence platforms such as Power BI. * Experience designing secure AI-ready data architectures, including retrieval patterns, agent or tool integrations, natural-language analytics, vector or unstructured data capabilities, and Model Context Protocol (MCP) configurations. * Experience designing enterprise semantic layers, governed metrics, metadata, lineage, data quality, privacy controls, and self-service analytics capabilities. * Experience simplifying or modernizing complex data platforms and leading enterprise-scale platform adoption or migration initiatives. * Relevant Snowflake, cloud architecture, security, data engineering, or Power BI certifications are beneficial but not required. ## Description The Principal Analytics Engineer is the organization's most senior individual contributor for the enterprise data platform and serves as the end-to-end technical owner of Snowflake and its supporting ecosystem. This role is accountable for platform architecture, ingestion, data transformation, performance, reliability, security, governance, cost optimization, and operational excellence. The position reviews and guides architectural decisions across the data team, establishes engineering standards, and enables trusted analytics and AI capabilities, including secure Model Context Protocol (MCP) configurations and governed access to enterprise data. Working closely across the entire data team and with technology, security, AI, and business partners, this role is critical to driving successful, scalable Snowflake adoption across the enterprise. What You Get to Do Every Day: * Own the strategy, architecture, administration, reliability, and continuous evolution of the enterprise Snowflake platform and its supporting data ecosystem. * Design and oversee scalable ingestion, transformation, orchestration, and data-serving patterns across Snowflake, Fivetran, Power BI, and complementary technologies. * Set and enforce platform standards for performance, workload management, reliability, observability, testing, deployment, disaster recovery, and cost optimization. * Own the technical implementation of Snowflake security, including roles and access controls, authentication, network policies, data protection, auditing, privacy, and secure data sharing in partnership with Information Security. * Serve as the senior architecture authority for the data platform by reviewing major designs, challenging tradeoffs, reducing unnecessary complexity, and ensuring decisions align with enterprise architecture, governance, and long-term maintainability. * Lead the technical enablement of AI use cases on governed enterprise data, including secure Model Context Protocol (MCP) server and client configurations, tool access patterns, data interfaces, and controls for AI-assisted workflows and agents. * Establish reusable engineering patterns, reference architectures, coding practices, documentation expectations, and review processes that improve quality and delivery across the data team. * Partner closely with analytics engineers, BI professionals, AI teams, application teams, infrastructure, security, and business stakeholders to deliver trusted platform capabilities and accelerate enterprise adoption. * Diagnose and resolve the most complex production, performance, integration, and security issues; lead root-cause analysis and drive durable remediation. * Provide deep technical mentorship and influence across the data team without direct people-management responsibility, raising engineering capability and guiding critical decisions. * Define and monitor platform health, adoption, service levels, cost, and value metrics; maintain a prioritized technical roadmap that supports successful Snowflake adoption across the enterprise.