Sr. Manager, Data & ML Engineering

Deckers Brands is committed to creating an inclusive workplace and is seeking a Senior Manager for Data & ML Engineering. This role leads the delivery and operational excellence of the company's modern data platform, focusing on building and maintaining scalable data pipelines for analytics and machine learning use cases.

Responsibilities:

• 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

Requirements:

• Bachelor's degree required, preferably in Computer Science, Engineering, or related technical field; Master's degree preferred
• 8 to 12 years of experience building enterprise-grade data platforms and pipelines
• 3 to 5+ years leading data engineering and/or analytics engineering teams in cloud-native environments
• Demonstrated hands-on experience using dbt as a primary transformation framework in production, including testing, documentation, CI/CD, and release practices
• Strong experience delivering data platforms on AWS (S3, Redshift, Glue, EMR, Lambda, Kinesis, SageMaker as applicable)
• Deep understanding of modern data modeling and analytics engineering concepts, including dbt best practices
• Strong AWS data engineering expertise including scalability, reliability, and cost optimization
• Strong leadership and people-management skills with a focus on coaching and developing talent
• Ability to drive technical excellence while balancing speed, quality, and operational stability
• Excellent problem-solving, analytical thinking, and decision-making skills
• Strong communication and influencing skills across technical and business stakeholders
• Comfortable working in a fast-paced, matrixed, and global environment
• AWS certifications (Data, Machine Learning, or Solution Architecture) are a plus
• Experience supporting ML initiatives through strong data foundations, feature readiness, and platform enablement is preferred