Principal Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the strategy, architecture, administration, reliability, and ongoing development of the enterprise Snowflake platform and its associated data ecosystem.

• Design and manage scalable ingestion, transformation, orchestration, and data-serving patterns utilizing Snowflake, Fivetran, Power BI, and other relevant technologies.

• Establish and uphold platform standards regarding performance, workload management, reliability, observability, testing, deployment, disaster recovery, and cost optimization.

• Lead the technical implementation of Snowflake security, covering roles and access controls, authentication, network policies, data protection, auditing, privacy, and secure data sharing.

• Act as the senior architectural authority for the data platform by reviewing significant designs, evaluating trade-offs, reducing complexity, and ensuring alignment with enterprise architecture and governance.

• Spearhead technical enablement for AI use cases on governed enterprise data, including secure configurations for MCP servers and clients, tool access patterns, data interfaces, and controls.

• Create reusable engineering patterns, reference architectures, coding standards, documentation expectations, and review procedures.

• Collaborate with analytics engineers, BI professionals, AI teams, application teams, infrastructure, security, and business stakeholders.

• Troubleshoot and resolve intricate production, performance, integration, and security challenges; lead root cause analysis and durable solutions.

• Provide in-depth technical mentorship and influence across the data team without direct people-management responsibilities.

• Define and track platform health, adoption, service levels, cost, and value metrics; maintain a prioritized technical roadmap.

⛳️ Requirements

• Bachelor's Degree.

• A minimum of 10 years of progressive experience in data engineering, analytics engineering, data platform engineering, cloud data architecture, or a closely related field, including ownership of critical production data platforms.

• Significant hands-on experience in architecting, administering, securing, optimizing, and operating Snowflake within an enterprise context.

• Proven experience in designing and managing production ingestion, transformation, orchestration, observability, and data-serving patterns across a contemporary cloud data stack.

• Demonstrated success as a senior technical authority by reviewing architecture, influencing cross-functional decisions, mentoring seasoned engineers, and leading the resolution of complex platform challenges.

• Experience collaborating with security, infrastructure, application, analytics, AI, and business teams to provide secure, governed, and widely adopted enterprise data capabilities.

• Expert-level knowledge of Snowflake encompassing architecture, administration, virtual warehouses, workload management, performance tuning, cost governance, data sharing, replication, recovery, security, monitoring, and operational support.

• Proficient in SQL with a deep understanding of data modeling, ingestion, transformation, orchestration, testing, observability, version control, release automation, and production engineering practices.

• Extensive knowledge 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 understanding of AI-enablement patterns for enterprise data, including secure MCP configurations, governed data access, retrieval and tool-integration patterns, and controls for AI-assisted applications and agents.

• Exceptional architectural judgment and the ability to assess trade-offs among simplicity, scalability, security, performance, cost, governance, resilience, and maintainability.

• Capacity to lead through technical influence, perform thorough design and code reviews, mentor experienced professionals, establish standards, and foster collaboration across teams without formal authority.

• Strong communication, consulting, and stakeholder management skills, with the ability to articulate complex platform decisions to both technical and executive audiences, linking engineering choices to business outcomes.

• Proven ownership, sound judgment, intellectual curiosity, and the ability to work independently on high-impact priorities while collaborating across the data team and enterprise.

• Relevant certifications in Snowflake, cloud architecture, security, data engineering, or Power BI are advantageous but not mandatory.

🏝️ Benefits

• Comprehensive compensation package.

• Comprehensive benefits package.

• 401k.

• PTO.

• Health & Wellness Days.

• Paid Volunteer Time Off.

• Continuing education and training.

• Hybrid / Remote work schedule.

• Paid Parental Leave.