Sr Data Modeler / Principal AI & Analytics Platform Engineer

Sunrise Systems, Inc. is seeking a highly experienced Principal AI & Analytics Platform Engineer to lead the architecture, engineering, and evolution of their enterprise AI and analytics platform. The role involves designing scalable cloud-native data platforms, AI-enabled applications, and modern analytics solutions, while partnering with business stakeholders to drive data-driven solutions.

Responsibilities:

• The Sr. Data Modeler works directly with business stakeholders to design data and analytics capabilities that support business strategies and to develop the data models and structures that enable data-driven solutions
• The Sr Data Modeler develops data models and structures that can be used within the business to find data driven solutions
• Architect, design, and build enterprise-scale AI and analytics platforms from the ground up
• Design secure, multi-tenant architectures supporting internal users and external customer-facing applications
• Build scalable cloud-native solutions supporting analytics, AI, machine learning, generative AI, automation, and operational intelligence
• Develop foundational data architectures supporting enterprise AI initiatives utilizing Snowflake, Snowpark, Cortex AI, LLMs, vector search, and modern AI frameworks
• Establish architecture standards emphasizing scalability, resiliency, security, governance, and cost optimization
• Evaluate emerging AI and cloud technologies while driving adoption of modern engineering practices
• Design, develop, and optimize enterprise data platforms utilizing Snowflake and cloud-native technologies
• Build and maintain high-volume ETL/ELT pipelines supporting analytics, reporting, AI, and operational workloads
• Model and optimize billions of rows of enterprise data using dimensional, normalized, and Data Vault methodologies
• Optimize Snowflake performance through clustering strategies, workload management, query optimization, caching, and cost management
• Develop solutions utilizing SQL, Python, Snowpark, APIs, automation frameworks, and cloud-native services
• Design and integrate AI-powered capabilities into enterprise platforms using Snowflake Cortex, LLM APIs, machine learning models, and modern AI frameworks
• Develop intelligent analytics experiences including predictive insights, natural language interfaces, AI copilots, and workflow automation
• Partner with Enterprise AI leaders to identify high-value AI use cases and translate business challenges into scalable AI-enabled solutions
• Build secure AI solutions aligned with enterprise governance, privacy, compliance, and responsible AI practices
• Continuously evaluate emerging AI technologies and recommend opportunities to improve business operations and customer experiences
• Champion AI-assisted software development using modern coding assistants while maintaining engineering quality through human oversight, testing, and optimization
• Build modern React applications optimized for large-scale analytical workloads
• Develop high-performance dashboards, interactive visualizations, and data-intensive user experiences
• Optimize rendering performance through virtualization, caching strategies, state management, and Web Workers
• Design, build, and optimize backend APIs using Python or Node.js (TypeScript)
• Deliver secure, performant, and scalable end-to-end applications supporting enterprise analytics and AI workloads
• Design and implement enterprise multi-tenant security architectures ensuring complete customer data isolation
• Develop row-level security (RLS), access controls, and governance frameworks in collaboration with Data Governance and Security teams
• Ensure AI and analytics platforms align with enterprise security, privacy, compliance, and regulatory standards
• Establish engineering best practices for architecture, software quality, performance, observability, and operational excellence
• Partner directly with business executives, product leaders, analytics teams, and technology organizations to translate strategic objectives into technical solutions
• Serve as a trusted advisor on enterprise AI, analytics, cloud modernization, and digital transformation initiatives
• Develop technical roadmaps aligning engineering investments with business priorities
• Present architecture strategies, AI opportunities, technical recommendations, business impacts, risks, and implementation plans to senior leadership, steering committees, and executive stakeholders
• Translate highly complex technical concepts into clear, business-focused communications appropriate for executive audiences
• Drive adoption of modern engineering practices, automation, DevOps, and AI-native development methodologies
• Lead proof-of-concepts, innovation initiatives, and technology evaluations
• Identify opportunities to improve platform scalability, reliability, performance, developer productivity, and operational efficiency
• Foster a culture of experimentation, continuous learning, and technical excellence
• Although this is an individual contributor role, it carries significant enterprise influence and leadership responsibilities
• Lead through technical expertise and influence rather than direct authority
• Mentor engineers and cross-functional teams on AI, cloud engineering, and modern software development practices
• Establish engineering standards, architectural patterns, and development best practices
• Drive organizational adoption of AI technologies through education, enablement, and technical leadership
• Train engineering teams and business stakeholders on AI capabilities, analytics platforms, and modern development workflows
• Delegate technical initiatives appropriately while enabling teams to independently deliver high-quality solutions
• Success will be measured not only by technical delivery, but by the ability to influence enterprise decisions, accelerate innovation, and enable business transformation through AI and data technologies

Requirements:

• 8+ years of experience in software engineering, data engineering, analytics engineering, or cloud platform development
• 5+ years of enterprise experience building solutions with Snowflake
• Expert-level SQL and Python development skills
• Strong experience with Node.js (TypeScript) or comparable backend technologies
• Deep expertise with Snowpark, Snowflake Cortex, Streams, Tasks, and enterprise Snowflake optimization
• Experience designing scalable enterprise data models including dimensional, normalized, and Data Vault architectures
• Extensive experience building enterprise ETL/ELT pipelines
• Experience with AWS, Azure, and/or Google Cloud Platform
• Experience designing APIs, automation frameworks, and cloud-native services
• Strong understanding of enterprise security, data governance, compliance, privacy, and multi-tenant architectures
• Experience implementing row-level security (RLS), data isolation, and secure data access models
• Expertise developing React applications optimized for large-scale analytical datasets
• Experience optimizing frontend performance using virtualization, advanced caching, state management, and Web Workers
• Hands-on experience integrating LLMs, AI services, machine learning platforms, and enterprise AI frameworks into production applications
• Experience leveraging AI-assisted development tools while maintaining high engineering standards through testing, review, and optimization
• Exceptional written, verbal, presentation, and executive communication skills
• Demonstrated ability to present technical strategy and architecture to VP and C-suite audiences
• Experience building enterprise AI platforms and AI engineering frameworks
• Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, semantic search, and AI orchestration frameworks
• Familiarity with MLOps, model lifecycle management, and AI governance practices
• Experience with Kubernetes, containerization, Infrastructure as Code, and CI/CD automation
• Experience supporting customer-facing SaaS analytics platforms
• Knowledge of observability, platform reliability engineering, and distributed systems architecture