Sr. Manager, Data & ML Engineering
Deckers Brands · California, United States
- Hybrid
- Full-time
- $190,000 / year
- California, United States
Job highlights
- Lead data and ML engineering on AWS.
- Focus on dbt for data transformation.
- Build scalable data pipelines.
- Manage and mentor a team.
- Drive data quality and ML readiness.
About the role
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.
The Role
Are you ready to shape the future of data and ML engineering 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.
Your Impact
- 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
Who You Are
- 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, SageMaker 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 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
What We'll Give You –
- Competitive Pay and Bonuses - We’ve created a variety of competitive compensation programs to foster career development, reward success and to show our employees just how much they’re valued.
- Financial Planning and wellbeing - No matter what financial goals our employees have set, we want to help them get there. Our plans provide powerful ways to protect income, pay for expenses and invest in the future.
- Time away from work - Sometimes we need time away to be with family, focus on our health or just simply recharge. Our plans support our employees’ needs to get out, get healthy and come back stronger than ever.
- Extras, discounts and perks - Being a valued member of the Deckers Brands team means more than just a paycheck. From generous discounts to community-based programs, we offer a variety of cool extras
- Growth and Development - Deckers Brands was built on the idea of pursuing passion. That’s why we offer extensive opportunities and support for personal and professional development.
- Health and Wellness - There’s nothing basic about our comprehensive health and wellness programs and offerings. While at work and at play, we aim to support a healthy lifestyle.
Salary Range
$170,000 - $190,000
The salary range posted reflects the minimum and maximum target for new hire salaries for this role in our Goleta, CA location. Individual pay will be determined by location and additional factors, including job related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary for your preferred location during the hiring process.
Equal Employment Opportunity
Diversity and inclusion are key to our success. We are proud to be an equal opportunity employer, and our employees are people with different strengths, experiences and backgrounds who share a passion for our brands. We welcome qualified applicants regardless of their race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, military or veteran status, mental or physical disability, medical condition and all the other beautiful parts of your identity.
Key skills/competency
- Data Engineering
- ML Engineering
- dbt
- AWS
- Data Pipelines
- Data Modeling
- Analytics Engineering
- Leadership
- Cloud Platforms
- Data Quality
Skills & topics
- Sr. Manager, Data & ML Engineering
- Data Engineering
- ML Engineering
- dbt
- AWS
- Data Pipelines
- Data Modeling
- Analytics Engineering
- Cloud Platforms
- Data Quality
- Leadership
- Remote
- Deckers Brands
How to get hired
- Tailor your resume: Highlight experience with AWS, dbt, data pipelines, and ML engineering. Quantify achievements in leadership roles.
- Craft a compelling cover letter: Express your passion for Deckers Brands and how your skills align with the Senior Manager, Data & ML Engineering role.
- Prepare for technical interviews: Be ready to discuss dbt best practices, AWS data services, data modeling, and MLOps concepts.
- Showcase leadership: Demonstrate your experience managing and mentoring data engineering teams and driving technical excellence.
- Research Deckers Brands: Understand their mission, values, and recent achievements to show genuine interest.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key technical skills required for the Senior Manager, Data & ML Engineering role at Deckers Brands?
- The Senior Manager, Data & ML Engineering role at Deckers Brands requires strong hands-on experience with AWS data services (S3, Redshift, Glue, EMR, Lambda, Kinesis, SageMaker), proficiency in dbt as a primary transformation framework, deep understanding of modern data modeling and analytics engineering concepts, and expertise in building and managing scalable data pipelines. Experience supporting ML initiatives through feature readiness and platform enablement is also highly valued.
- What is the expected level of experience for the Senior Manager, Data & ML Engineering position at Deckers Brands?
- Deckers Brands is seeking a candidate with 8 to 12 years of experience building enterprise-grade data platforms and pipelines, and 3 to 5+ years specifically leading data engineering and/or analytics engineering teams in cloud-native environments. A Bachelor's degree in a related technical field is required, with a Master's degree preferred.
- Does Deckers Brands offer remote work for the Senior Manager, Data & ML Engineering role?
- Yes, the Senior Manager, Data & ML Engineering position at Deckers Brands is a remote role, but applicants must reside in one of the approved states: Arizona, California, Colorado, Indiana, Massachusetts, Minnesota, New York, Oregon, Pennsylvania, Texas, Utah, or Washington.
- What is the salary range for the Senior Manager, Data & ML Engineering position at Deckers Brands?
- The posted salary range for the Senior Manager, Data & ML Engineering role at Deckers Brands is $170,000 - $190,000 annually. The exact salary will depend on factors such as location, experience, and education.
- What are the opportunities for growth and development in the Data & ML Engineering team at Deckers Brands?
- Deckers Brands offers extensive opportunities and support for personal and professional development, including coaching, performance management, and career development for team members. The company emphasizes pursuing passion and provides a clear path for growth within the organization.
- What is the importance of dbt in the Senior Manager, Data & ML Engineering role at Deckers Brands?
- dbt is a critical component of the Senior Manager, Data & ML Engineering role at Deckers Brands, serving as the primary transformation framework for their modern data platform. The role involves establishing and enforcing dbt development standards, including model design, documentation, testing, CI/CD, and release practices.
- How does Deckers Brands approach diversity and inclusion for the Senior Manager, Data & ML Engineering role?
- Deckers Brands is committed to diversity and inclusion, valuing the unique identities, experiences, and perspectives of all employees. They strive to create an inclusive and equitable workplace where everyone can 'Come as They Are', believing that diverse perspectives lead to better outcomes.