Deckers Brands · 2 hours ago
Sr. Manager, Data & ML Engineering
Deckers Brands is committed to inclusivity and valuing every employee. As the Senior Manager of Data & ML Engineering, you will lead the development of a modern data platform, driving innovation in analytics and machine learning while ensuring operational excellence and data governance.
ApparelFashionLifestyleLogisticsManufacturingRetailTextiles
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
Qualification
Required
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
Preferred
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
Benefits
Competitive Pay and Bonuses
Financial Planning and wellbeing
Time away from work
Extras, discounts and perks
Growth and Development
Health and Wellness
Company
Deckers Brands
Footwear & Apparel Company
H1B Sponsorship
Deckers Brands has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (21)
2024 (20)
2023 (19)
2022 (27)
2021 (21)
2020 (17)
Funding
Current Stage
Public CompanyTotal Funding
unknown1993-10-22IPO
Recent News
The Motley Fool
2025-11-16
Company data provided by crunchbase