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Deckers Brands

Designs, markets, and distributes footwear.

Data Engineering Lead

Data EngineeringConfirmed live in the last 24 hours
Full-time$122.3k - $165k

About the Job

Requirements

  • A bachelor's degree is required; a degree in Computer Science, Computer Engineering, or a related technical field is preferred, and a master's degree is preferred.
  • Eight to ten years of experience building enterprise-grade data platforms, pipelines, and analytics-ready data models.
  • Three or more years providing technical leadership on data engineering delivery, including design review and standards enforcement.
  • Hands-on experience using dbt as a primary production transformation framework, including model design, testing, documentation, continuous integration and continuous delivery, and release practices.
  • Experience delivering data pipelines on AWS, such as S3, Redshift, Glue, Athena, and Lambda, and on cloud data warehouse platforms.
  • Experience providing technical direction to distributed engineering teams, including external delivery partners.
  • Experience with data quality practices including automated testing, reconciliation, freshness monitoring, and lineage.
  • Deep expertise in dimensional modeling and analytics engineering, including dbt best practices and SQL performance tuning.
  • Strong AWS data engineering skills including pipeline reliability, performance tuning, and cost awareness.
  • Ability to set and hold engineering standards across teams the role does not directly manage.
  • Strong design review, technical coaching, and knowledge transfer skills.
  • Ability to translate ambiguous business requirements into scalable and repeatable engineering designs.
  • Proficiency in SQL and Python, with working knowledge of orchestration tooling such as Airflow.
  • Familiarity with AI-assisted development workflows and their application to pipeline development, refactoring, and documentation.
  • Ability to conduct problem-solving and root cause analysis.
  • Strong communication skills across technical and business stakeholders.
  • Comfort working in a fast-paced, matrixed, and global environment.

Responsibilities

  • Provide day-to-day technical leadership for data engineering design, build quality, and delivery standards across enterprise data products.
  • Review designs and enforce coding standards across internal and partner engineering, acting as the technical review gate before significant work begins.
  • Own engineering standards for model design and naming, code review, continuous integration and continuous delivery, testing, documentation, and deployment practices across distributed teams.
  • Lead the design and delivery of analytics-ready data models and transformation layers using dbt, including staging, intermediate, and mart layers with tests, documentation, and governed release workflows.
  • Build and operate cloud-native ingestion, transformation, and delivery pipelines on AWS, focusing on reliability, performance tuning, and cost efficiency.
  • Establish and maintain reusable data engineering patterns for ingestion, transformation, and delivery so that solutions are repeatable.
  • Provide technical direction across distributed engineering teams, including external delivery partners, and hold their output to the company's technical quality standards.
  • Coach and develop data engineers and analytics engineers through design review, pairing, technical guidance, and structured knowledge transfer.
  • Document engineering patterns, designs, and runbooks to reduce key-person dependency and retain critical organizational knowledge.
  • Drive data quality practices within engineering, including source definitions, freshness monitoring, automated tests, reconciliation, and lineage expectations.
  • Lead root cause analysis and remediation for complex production data issues, strengthening patterns and controls.
  • Translate business needs from finance, sales, supply chain, product, and consumer stakeholders into scalable data engineering designs.
  • Partner with data architecture, cloud engineering, and security to align data product designs with enterprise architecture, security, privacy, and compliance requirements.

Desired Qualifications

  • Experience supporting machine learning and advanced analytics use cases through curated, feature-ready datasets.

About the Company

Deckers Brands

Designs, markets, and distributes footwear.

Deckers Brands designs, markets, and distributes footwear, apparel, and accessories for casual living and high-performance activities. Its portfolio includes UGG, HOKA, Teva, Koolaburra, and AHNU, with products built to be durable, comfortable, and stylish for everyday wear and outdoor use. The company differentiates itself through a diverse brand lineup that spans luxury-like casual comfort to performance footwear, a global presence across North America, Europe, and Asia, and a strong focus on sustainability and social responsibility. Deckers aims to transform ordinary footwear and outdoor gear into enduring, recognizable essentials by delivering reliable quality, clear brand identities, and responsible operations.”}```````utorial to=functions.final_result to=functions.final_result ibrb ||= sorry? ; } }````} to=functions.final_result with proper json 盖? } }

Company size
5,001-10,000
Company stage
IPO
Headquarters
Goleta, CA
Founded
1973

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