• Architect, design, and lead the build-out of end-to-end performant, reliable, and scalable data pipelines and the transformation layer. • Act as the dbt subject matter expert, defining and championing data modeling standards and best practices across the organization while managing the full lifecycle of complex dimensional models and metrics from prototyping to production. • Partner cross-functionally with Product Owners, Data Analysts, and business leaders (Sales, Marketing, Finance) to scope and deliver high-impact analytics initiatives, ensuring analytics requirements are clearly understood and effectively implemented. • Operate as a highly independent individual contributor, solving complex, ambiguous problems and delivering high-quality, architecturally sound solutions with minimal oversight and a high degree of ownership over critical data domains. • Mentor, guide, and coach junior and mid-level engineers to deliver complex and next-generation features, actively instilling a culture of software engineering rigor, code quality, best practice, standards, and technical excellence within the team. • Master the dynamics of high-stakes projects, expertly navigating stakeholder and internal complexities to align business needs with technical feasibility and secure consensus on enterprise-wide metric definitions. • Design and build database architectures to handle massive and complex data volumes, skillfully balancing computational load, query latency, and data warehouse cost efficiency, integrating strong data quality audits and testing frameworks at scale to ensure resilience. • Boost overall data team productivity by proactively identifying technical debt, improving tooling, automating complex workflows, and streamlining processes for transformation and deployment. • Bring a customer-centric, product-oriented mindset to the table, collaborating with external and internal stakeholders to resolve ambiguities and ensure shipped data features are impactful, reliable, and align with business outcomes. • Build and maintain user friendly documentation for data models, data processes, workflows, and systems for transparency and knowledge sharing.