• Lead architecture, design, and implementation of enterprise-scale technology solutions. • Conduct business and technical discovery sessions with stakeholders to identify requirements and solution strategies. • Develop solution architectures supporting cloud-native, hybrid, and enterprise application environments. • Provide technical leadership throughout the full software development lifecycle, from planning and design through deployment and support. • Evaluate emerging technologies and provide recommendations regarding adoption of new tools, platforms, and methodologies. • Support modernization initiatives involving cloud engineering, containerization, microservices, DevSecOps, and platform automation. • Design solutions utilizing multiple data stores, including relational and NoSQL technologies. • Develop architecture standards, interface standards, performance standards, and quality assurance practices. • Support implementation of enterprise data architecture, data governance, and metadata management strategies. • Provide guidance regarding data integration, data conversion, and enterprise information architecture initiatives. • Collaborate with development, infrastructure, cybersecurity, and business teams to ensure successful solution delivery. • Present technical recommendations, roadmaps, and architecture strategies to executive leadership and stakeholders. • Support implementation of AI and machine learning capabilities where appropriate to enhance mission outcomes.

• Lead technical discovery, solution design, and proof-of-value engagements with enterprise customers across all industries • Translate complex business requirements into architectures leveraging the Snowflake Data Cloud (data engineering, data science/AI/ML, data sharing, applications, and security/governance) • Deliver compelling technical presentations, demos, and workshops to audiences ranging from individual contributors to C-suite executives • Partner with Account Executives to drive pipeline, accelerate deals, and close business • Serve as the voice of the customer back to Product and Engineering teams • Build and maintain reusable assets: demo environments, reference architectures, and solution accelerators • Stay current on competitive landscape, industry trends, and emerging capabilities across the data & AI ecosystem

• Develop and maintain responsive web applications using Next.js and Node.js. • Write clean, maintainable code in Python for backend services and data processing scripts. • Build and monitor automated workflows and data pipelines using Airflow and dbt. • Design and implement secure, scalable RESTful APIs. • Manage and deploy applications within an AWS environment, ensuring cloud best practices are followed. • Optimize database performance and manage data migrations in Postgres. • Quickly learn and implement new frameworks or tools based on project-specific requirements

• Lead discovery workshops to understand client objectives, existing systems, data flows, and constraints. • Define target-state architecture for CRM, CDP, and marketing automation, including integration patterns, governance, and scalability considerations. • Translate business problems into technical solution options, with clear trade-offs, effort estimates, and risks. • Guide implementations end-to-end, from documentation and planning through detailed requirements and support for build. • Produce high-quality technical artifacts including architecture diagrams, data flow maps, event and identity models, and implementation roadmaps. • Write clear technical requirements for engineers, partnering with technical project management to scope, sequence, and deliver work. • Partner with client stakeholders to drive decisions and keep delivery aligned to outcomes, timelines, and dependencies. • Architect and support integrations across the MarTech stack, including CDPs, marketing automation platforms, analytics, attribution, and enrichment tools. • Design data schemas and event tracking plans that support lifecycle use cases and analytics needs. • Support ETL and reverse ETL patterns to activate data into downstream destinations. • Ensure solutions account for omnichannel transactional and marketing messaging, customer journeys, user states, and event-driven automation.