Owns the enterprise Snowflake data platform end to end, including architecture, ingestion, transformation, security, governance, reliability, performance, cost optimization, and AI enablement. Establishes engineering standards, reviews architecture, resolves complex production issues, mentors data professionals, and leads cross-functional adoption of scalable, governed analytics capabilities. The role provides senior technical influence without direct people management and supports secure MCP-based AI integrations.
Our Story:
Crisis Prevention Institute, Inc. (CPI) is the worldwide leader in evidence‑based de‑escalation and crisis prevention training and dementia care services. Our programs teach professionals the skills to recognize, prevent, and respond to crises in the workplace. Since 1980, we’ve helped train more than 17 million people across service‑oriented industries including education, health care, behavioral health, long‑term care, human services, security, corporate, and retail.
At CPI, we are dedicated to changing behaviors and reducing conflict for the Care, Welfare, Safety, and Security of everyone. We believe empathy, meaningful connections, personal safety, and security are the antidotes to fear and anxiety. This philosophy is central to everything we do and traces back to our beginning.
As a member of the team, you can expect to:
The Role:
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:
Crisis Prevention Institute, Inc. (CPI) is the worldwide leader in evidence‑based de‑escalation and crisis prevention training and dementia care services. Our programs teach professionals the skills to recognize, prevent, and respond to crises in the workplace. Since 1980, we’ve helped train more than 17 million people across service‑oriented industries including education, health care, behavioral health, long‑term care, human services, security, corporate, and retail.
At CPI, we are dedicated to changing behaviors and reducing conflict for the Care, Welfare, Safety, and Security of everyone. We believe empathy, meaningful connections, personal safety, and security are the antidotes to fear and anxiety. This philosophy is central to everything we do and traces back to our beginning.
As a member of the team, you can expect to:
- Make a difference through your work — You’ll be proud to tell your family and friends what you do.
- Gain significant career experience within a fast‑growing organization — From entry‑level roles to executive leadership.
- Feel fulfilled and have fun — We work hard but make time to build meaningful relationships and celebrate wins.
The Role:
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.
- 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.
- 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.
- 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
Similar Jobs
Healthtech
Provides technical leadership for enterprise analytics by architecting SQL-based transformations, scalable data models, semantic layers, and governed datasets. Builds analytics products supporting healthcare KPIs, patient journeys, scheduling, retention, and operational decisions. Establishes analytics engineering standards, testing, documentation, lineage, and code-review practices; troubleshoots data-quality issues; partners with business and technical stakeholders; and mentors analysts in SQL, dimensional modeling, dbt, and governed data-product development.
Top Skills:
Amazon RedshiftAutomated TestingCi/CdData Orchestration ToolsDatabricksDbtEhr SystemsGitPower BISnowflakeSQL
Information Technology • Legal Tech • Analytics
Own the analytics product vision, roadmap, prioritization, and delivery across Clinical Solutions. Develop customer-facing and internal dashboards, KPIs, embedded insights, and generative AI capabilities that improve healthcare decision-making. Translate strategy into execution with technology, informatics, analytics, commercial, and customer success teams. Define product outcomes, ensure data quality and governance, support commercialization and adoption, and monitor healthcare technology and regulatory trends.
Top Skills:
Ai/MlFhirGenerative AiHl7LoincSnomed
Artificial Intelligence • Healthtech • Information Technology • Other • Analytics
Own the analytics product vision, roadmap, prioritization, and delivery across Clinical Solutions. Lead customer-facing and internal dashboards, KPIs, embedded insights, data quality, governance, and generative AI applications. Partner with technology, informatics, analytics, commercial, sales, marketing, and customer success teams to deliver measurable clinical and business outcomes. Represent analytics priorities, drive adoption, and monitor healthcare technology, regulatory, and industry trends.
Top Skills:
Ai/MlAnalytics PlatformsFhirGenerative AiHl7LoincSnomed
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
