Data Engineering Lead

🕒 September 24

🌵 Arizona, California, +9 more states – Remote

🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🗽 New York – Remote 🌲 Oregon – Remote 🍂 Massachusetts – Remote ❄️ Minnesota – Remote 🔔 Pennsylvania – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ☕ Washington – Remote

💵 $122.3k - $165k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Deckers Brands

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1973

🏭 Manufacturing

📦 Logistics

👗 Fashion

Manufacturing • Logistics • Fashion

Deckers Brands is a global leader in designing, marketing, and distributing innovative footwear, apparel, and accessories. Known for its high-quality products and trendsetting designs, Deckers Brands encompasses a portfolio of well-known brands that appeal to diverse consumer segments worldwide.

📋 Description

• 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

• 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

• 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