• Participate as a Snowflake Engineer in the project team and provide agile software delivery, best-practice expertise to deliver results for an organization. • Play a key role in delivering data-driven solutions for our client. • Proactively develop relationships with clients to understand their needs and effectively translate those needs into outcome driven solutions. • Provide expertise as a Snowflake SME to solve complex business issues that translate into data integration, processing, analytics and storage designs in Microsoft Azure. • Design, develop, and operate highly reliable large scale data lake systems. • Embrace Snowflake innovations with open source standards and tool sets. • Ensure all deliverables are high quality by setting development standards, adhering to the standards and participating in code reviews. • Participate in integrated validation and analysis sessions of components and subsystems on cloud servers. • Ability to perform market research and make specific recommendations including a SWOT Analysis (Strength, Weakness, Opportunity, Threat).

- Create the high-level design of integration solutions and guide implementation teams on the choice of Mule components and patterns to use in the detailed design and implementation - Work with technical and non-technical stakeholders to translate functional and non-functional requirements into integration interfaces and implementations - Apply standard development methods covering the full development lifecycle (project preparation, analysis, design, development, testing, deployment, and support) to ensure solution quality. - Advise technical teams on performance, scalability, reliability, monitoring and other operational concerns of integration solutions on Anypoint Platform. - Design reusable assets, components, standards, frameworks, and processes to support and facilitate API and integration projects. - Ensure that a quality solution is delivered in a timely manner, within budget and according to the customer satisfaction.

• Tutor architectural courses to students in 1:1 or group settings • Provide virtual instruction from home • Work on a flexible schedule, typically M/W/F and weekends (PST) • Conduct sessions that are 1hr+ in duration

• Collaborate with the Chief Architect to define and execute the Data, Integration and AI strategy • Design and architect solutions for our SaaS platform, ensuring scalability, performance, security, and cost-efficiency • Work with engineering teams to implement architecture patterns and best practices • Contribute to aligning target architecture and AI initiatives across the product portfolio • Implement cloud transformation initiatives leveraging Kubernetes and related cloud-native technologies • Design and integrate AI-powered capabilities (e.g., predictive analytics, intelligent automation, LLM-based virtual assistants) into specific product areas • Implement flexible architecture patterns that support deployment across multiple cloud providers (Azure or comparable AWS/GCP), private cloud and on-premises environments • Develop platform components that abstract cloud-specific dependencies while leveraging PaaS where appropriate • Apply FinOps practices to optimize cloud spend while maintaining performance and reliability • Create and maintain comprehensive architecture documentation for assigned product areas • Contribute to the metrics-driven governance framework to measure architectural effectiveness • Support technical due diligence (Tech DD) activities for potential acquisitions (M&A) • Mentor and coach engineering teams, ensuring architectural practices and responsible AI principles are embedded in development processes • Participate in internal AI and architecture communities, collaborating with engineering teams, Cloud Operations, and key stakeholders.