• Own and manage the data engineering backlog—prioritize stories, define acceptance criteria, and ensure delivery of pipelines and platform capabilities that accelerate data availability and quality. • Partner with Business Units, Analytics, and Tech Leadership to ensure data products are trusted, timely, and aligned with business priorities. • Collaborate with Data Engineers, Tech Leads, and Architects to translate technical vision into actionable deliverables for ingestion, transformation, orchestration, and serving layers. • Advocate for governed, scalable, and AI-ready data—partnering with Collibra and platform teams to ensure compliance and discoverability. • Champion AI-assisted development and automation (e.g., dbt auto-tests, Databricks notebooks, CI/CD intelligence, metadata lineage) to improve team velocity and reduce manual workload. • Leverage AI/ML-based monitoring and observability tools to enhance data reliability, anomaly detection, and operational performance. • Drive the Data Platform roadmap, aligning across engineering, analytics, and business stakeholders with clear transparency and measurable impact. • Foster a culture of continuous improvement, using metrics and retrospectives to increase throughput, quality, and predictability of delivery. • Represent the engineering voice in cross-functional planning and communicate technical dependencies, risks, and opportunities clearly. • Mentor junior Scrum Masters and influence agile practices to enhance team productivity and engagement.