Sr. Manager, Data & ML Engineering

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.

Are you ready to shape the future of data and machine learning at Deckers Brands? The Senior Manager, Data & ML Engineering leads the delivery and operational excellence of Deckers’ modern data platform, with a strong emphasis on dbt as the primary transformation framework and an AWS-native architecture. This role is accountable for building and maintaining scalable, reliable, and governed data pipelines that power analytics, reporting, and future machine learning use cases.

This role will initially focus on establishing a strong, trusted analytics foundation through robust ingestion, modeling, testing, documentation, and deployment practices. As the platform matures and core data products stabilize, the role will progressively expand to enable machine learning capabilities through feature readiness, curated datasets, and foundational MLOps patterns in partnership with Data Science and analytics teams.

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…