Data Engineering Lead

Deckers Brands

. Provide day-to-day technical leadership for data engineering design, build quality, and delivery standards across enterprise data products .

Posted 9/24/2026full-timeRemote • United StatesSenior💰 $122,300 - $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering leadership, focusing on the design and delivery of analytics-ready data models and cloud-native data pipelines. Proficient in enforcing engineering standards and driving data quality practices across distributed teams.

Highest-signal resume keywords

Data Engineering LeadershipAWS Data Pipeline DevelopmentDbt Transformation FrameworkSQL Performance TuningTechnical Coaching and Knowledge Transfer

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSQLPythonDimensional ModelingAutomated TestingData Quality PracticesCI/CDRoot Cause AnalysisAnalytics EngineeringFeature-Ready Datasets

Soft Skills

Problem-SolvingCommunication SkillsTechnical Coaching

Tools & Technologies

AWSDbtAirflow

Industry Keywords

Enterprise Data ProductsData ArchitectureCompliance RequirementsCloud Data WarehouseData Transformation

Tech Stack

Tools & technologies

AirflowAWSCloudPythonSQL

About the role

Key responsibilities & impact

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, CI/CD, testing, documentation, and deployment practices
Lead the design and delivery of analytics-ready data models and transformation layers using dbt
Build and operate cloud-native ingestion, transformation, and delivery pipelines on AWS
Establish and maintain reusable data engineering patterns for ingestion, transformation, and delivery
Provide technical direction across distributed engineering teams and external delivery partners
Coach and develop data engineers and analytics engineers through design review, pairing, technical guidance, and knowledge transfer
Document engineering patterns, designs, and runbooks to reduce key-person dependency
Drive data quality practices including source definitions, freshness monitoring, automated tests, reconciliation, and lineage
Lead root cause analysis and remediation for complex production data issues
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 designs with enterprise architecture, security, privacy, and compliance requirements

Requirements

What you’ll need

Bachelor’s degree required, preferably in Computer Science, Computer Engineering, or a related technical field
8–10 years of experience building enterprise-grade data platforms, pipelines, and analytics-ready data models
3+ years providing technical leadership on data engineering delivery, including design review and standards enforcement
Hands-on experience using dbt as a primary transformation framework in production, including model design, testing, documentation, CI/CD, and release practices
Strong experience delivering data pipelines on AWS and 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
Experience supporting machine learning and advanced analytics use cases through curated, feature-ready datasets is preferred
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
Excellent problem-solving and root cause analysis skills
Strong communication skills across technical and business stakeholders
Comfortable working in a fast-paced, matrixed, and global environment
Must reside in one of the approved states: Arizona, California, Colorado, Indiana, Massachusetts, Minnesota, New York, Oregon, Pennsylvania, Texas, Utah, or Washington

Benefits

Comp & perks

Competitive compensation programs and bonuses
Financial planning and wellbeing programs
Income protection, expense support, and investment plans
Time-away-from-work programs
Generous discounts
Community-based programs
Personal and professional development opportunities and support
Comprehensive health and wellness programs and offerings