• Own the technical customer relationship • Lead technical discovery with customers to understand workflows, systems, constraints, data environments, and success criteria. • Translate ambiguous business problems into clear solution architectures and implementation approaches. • Build credibility with both executive and technical stakeholders by clearly articulating how Wand works and where it creates differentiated value. • Partner closely with Sales on strategic deals and with Customer Success on long-term customer success and expansion. • Design scalable solution architectures for enterprise deployments using Wand’s platform, including workflows, agents, integrations, and governance requirements. • Define the technical approach for proofs of concept, pilots, and production rollouts. • Ensure solution designs are realistic, robust, measurable, and aligned with customer environments. • Help customers navigate integration, security, reliability, and operationalization considerations. • Define technical proof strategies for enterprise opportunities, including what needs to be validated for a customer to move forward. • Establish clear POC success criteria and benchmarks across dimensions such as accuracy, latency, coverage, usability, reliability, and business impact. • Help create a consistent “proof-to-contract” standard across the organization.

• Be the advocate for AI adoption across Asaas’ operational processes. • Work collaboratively with stakeholders from multiple Asaas business areas to identify opportunities to solve real problems using AI, with a focus on achieving operational efficiency gains. • Identify process bottlenecks and design solutions to address them, monitoring the direct impact on operational efficiency and process quality. • Manage the backlog of internal AI initiatives using prioritization frameworks to ensure focus on the highest-impact deliveries. • Negotiate deadlines, scopes, and resources with leaders from other areas to ensure aligned expectations. • Work closely with the AI technical team to validate solution feasibility and ensure business requirements are met in developed solutions.

• Responsible for ensuring technical solutions are aligned with industry-wide best practices. • Ensure end-to-end solution designs align with clients’ technology strategies and requirements. • Leading and inspiring other data professionals to deliver high-quality work.

• Lead engagements from discovery to delivery with full ownership and accountability. • Architect, implement, and optimize large-scale Spark/Databricks workloads focusing on scalability and cost-efficiency. • Apply expert-level Spark fundamentals to troubleshoot and tune distributed data jobs and SQL workloads. • Design and execute PoCs and workshops to demonstrate solution vision and inspire customer confidence. • Act as a technical advocate for customers, anticipating issues and applying creative, data-driven solutions. • Collaborate with product and engineering teams to improve customer experience and platform features. • Champion best practices in PySpark, Databricks, and Lakehouse design while mentoring junior engineers.