Sr. Manager, Data & ML Engineering

Overview

At Deckers Brands, Together, Every Step is a promise kept that every employee can bring their authentic self, is valued and supported, as a whole person, at work and beyond. Together, Every Step is how we continue to deliver exceptional business results, experience an amazing place to work, and have a positive impact on the communities and world around us.

Job Title: Sr. Manager, Data & ML Engineering

Reports to: Director, Data Platforms & Engineering

Location: United States (Remote)

Interested applicants must reside in one of the following approved states:
Arizona, California, Colorado, Indiana, Massachusetts, Minnesota, New York, Oregon, Pennsylvania, Texas, Utah, Washington

The Role

Are you ready to shape the future of data and machine learning at Deckers Brands? As the Senior Manager, Data & ML Engineering, you’ll lead the delivery and operational excellence of our modern data platform, driving innovation and reliability across analytics, reporting, and machine learning. You’ll be at the forefront of building scalable, governed data pipelines using dbt and AWS-native architecture, laying the foundation for advanced analytics and future ML capabilities.

This is your opportunity to make a lasting impact—establishing trusted data practices, enabling business insights, and empowering teams to unlock the full potential of data.

We celebrate diversity--of your background, your experiences and your unique identity. We are committed to ensuring an inclusive and equitable workplace where all of our employees can Come as They Are. We believe that when we bring our different perspectives to work, we are truly Better Together.

• 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

• Bachelor’s degree required, preferably in Computer Science, Engineering, or related technical field;
  Master’s degree preferred
• AWS certifications (Data, Machine Learning, or Solution Architecture) are a plus
• 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, Sage Maker as applicable)
• Experience supporting ML initiatives through strong data foundations, feature readiness, and platform enablement is preferred
• 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…