Sr. Manager, Analytics & BI Engineering

Deckers•Goleta, CA

6d•$137,500 - $185,600•Remote

About The Position

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 As the Sr. Manager, Analytics & BI Engineering, you will own the engineering capability for governed metrics and reporting delivery at Deckers. You’ll lead the implementation of enterprise metric definitions in the semantic layer, certify and enforce them, and ensure consistency across all reporting assets. This role is pivotal in building trust in our data, empowering business decisions, and developing analytics capability across the organization. You’ll direct both internal analytics engineering staff and an external BI delivery bench, setting standards, reusable patterns, and quality controls that drive reliable, impactful reporting. 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.

Requirements

Bachelor’s degree required, preferably in Computer Science, Engineering, Information Systems, or a related technical field; Master’s degree preferred.
8–12 years of experience building enterprise metrics, reporting, and business intelligence solutions.
3–5+ years leading analytics engineering, BI engineering, or reporting teams.
Hands-on experience owning an enterprise reporting platform such as Power BI, Tableau, Looker, or Qlik, including content governance, dataset certification, row-level security, and performance tuning.
Experience with semantic layer or OLAP modeling technology such as AtScale, dbt Semantic Layer, Cube, LookML, or Analysis Services.
Experience directing external delivery partners or contractor benches, including capacity planning, work allocation, and quality management.
Experience leading an analytics or insights team that serves business functions directly, including translating ambiguous business questions into defined, testable metrics.
Experience building analytics capability within business functions and transitioning ownership is preferred.
Experience working with cloud data platforms, preferably AWS, and with dbt-modeled data.
Deep expertise in dimensional modeling, semantic modeling, and metric definition, including SQL and a BI calculation language such as DAX or MDX.
Strong understanding of enterprise BI platform architecture, content governance, and performance optimization.
Ability to create reusable patterns and standards that scale delivery across internal and partner teams.
Strong delivery partner and contractor management skills, including capacity planning and quality control.
Strong leadership and people-management skills, with a focus on coaching and developing talent.
Ability to operate within a governance model owned by others while holding a firm line on engineering standards.
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.

Responsibilities

Own the semantic layer as the engineered source of enterprise metric definitions, including model design, technical certification, and consistent enforcement across every reporting asset.
Implement metric definitions set by data governance and data product functions, providing engineering input to resolve conflicting definitions across brands and business functions.
Own metric and report level quality, including reconciliation to the source of truth, definition consistency, and certification criteria for reporting assets.
Own the correctness, performance, and maintainability of reporting assets produced across data product teams, from certified data products through to production reporting.
Define and enforce engineering standards for metrics and reporting, covering model design, calculation logic, visual design, documentation, testing, source control, and release practices.
Own workspace structure, content organization, dataset certification and promotion, and the access and security model for the reporting platform.
Manage and mentor analytics engineers, BI developers, and analysts through coaching, performance management, and career development.
Establish metrics engineering as a defined craft within the organization, with its own standards, skills development, and career path.
Build the delivery model and intake process for metrics and reporting work, translating business needs into prioritized and sequenced delivery.
Lead the analytics function within the pillar, serving business areas with analysis and reporting built on certified metrics.
Build analytics capability inside business functions, defining maturity criteria and transition paths for moving analytics ownership closer to the business.
Direct the external business intelligence delivery bench, including capacity planning, work allocation, quality review, and partner performance management.
Supply metrics and reporting engineering capability into cross-functional data product teams, building durable domain knowledge.
Build and maintain reusable semantic models and reporting delivery patterns for consistent, performant, and repeatable output.