Sr Data Modeler / Principal AI & Analytics Platform Engineer

• Advanced SQL
• Data Modeling
• Datavault 2.0
• ER Studio
• Python for Data Analysis
• Snowflake Data Warehouse
• Vaultspeed

• Looking to convert the right person, pay rate max $71/hr, if convert would be around $130k.
• Huge plus if they have AI Engineering experience.
• Person will be working 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.
• If have AI experience they will be implementing AI interfaces for stakeholders. Please look at the must have list.

• 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.

• Experience Level: Principal / Lead Individual Contributor (8+ Years)

• We are seeking a highly experienced Principal AI & Analytics Platform Engineer to lead the architecture, engineering, and evolution of our enterprise AI and analytics platform. This is a strategic, hands-on technical leadership role responsible for designing scalable cloud-native data platforms, AI-enabled applications, and modern analytics solutions that drive business transformation.
• As a Principal Individual Contributor, you will operate as a trusted technical advisor, partnering closely with executive leadership, business stakeholders, product teams, data scientists, and engineering organizations to define and implement enterprise AI and analytics strategies. You will design and build secure, high-performance platforms capable of processing billions of rows of data while enabling advanced analytics, generative AI, machine learning, and intelligent automation across the organization.
• This role combines deep expertise in software engineering, cloud data platforms, enterprise architecture, AI integration, and executive communication. The ideal candidate thrives in ambiguity, embraces innovation, actively leverages AI-assisted development, and possesses the ability to translate complex technical concepts into measurable business outcomes.

• Architect, design, and build enterprise-scale AI and analytics platforms from the ground up.mo
• 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.

• 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.

• The Principal AI & Analytics Platform Engineer serves as a strategic technical leader who combines deep software engineering expertise with enterprise AI innovation. This individual builds secure, scalable platforms that power advanced analytics and AI capabilities while influencing technology strategy across the organization.
• Success requires balancing hands-on engineering excellence with architectural vision, executive communication, cross-functional collaboration, and enterprise-wide influence—delivering modern AI-powered solutions that create measurable business value and position the organization for long-term innovation.

• Work with business stakeholders to identify how data can be leveraged to improve decision making.
• Work with technology teams to analyze data requirements (functional and non-functional) and provide data architectural design solutions for business and technology initiatives.
• Assess the effectiveness and accuracy of data sources and data gathering techniques.
• Design data structures, data models and data pipelines, leveraging the support of subject matter experts to deliver business intelligence / data science capabilities for the organization.
• Create data models at all levels including conceptual, logical, and physical.
• Collaborate within an agile, multi-disciplinary team of data engineers, data analysts, UX designers and scrum master to deliver solution.
• Work with Data Scientists on optimizing batch and real-time processes for feature engineering, training models, and serving predictions.
• Research, promote, and develop data architecture best practices, guidelines, procedures and scalable frameworks.
• Participate in architecture, governance and design reviews.
• Participate in evaluations of existing and emerging analytical technologies and provide recommendations.

Pavan.p@sunrisesys.com