• Lead the design and delivery of analytics-ready data models and transformation layers using dbt as the standard framework • Establish and enforce dbt development standards, including model design, documentation, testing, CI/CD, and release practices • Own delivery and operations of scalable ingestion, transformation, and delivery pipelines on AWS, ensuring reliability, performance, and cost efficiency • Partner with Cloud Engineering and Security to ensure AWS data solutions meet security, privacy, and compliance requirements • Implement monitoring, alerting, incident response practices, and runbooks for dbt and AWS workloads to improve operational stability • Drive strong data quality practices including source definitions, freshness checks, automated tests, and data lineage expectations • Collaborate with business stakeholders to translate needs into prioritized roadmaps and delivered data products • Manage and mentor data engineers and analytics engineers through coaching, performance management, and career development • Promote disciplined engineering practices across the team including code review standards, documentation, automation, and reusable frameworks • Enable future machine learning use cases by ensuring curated datasets are ML-ready, including feature readiness and foundational requirements for model operationalization • Evaluate and introduce platform improvements that strengthen scalability, maintainability, governance, and developer productivity