Data Engineering Lead

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.

Reports to:

Sr. Manager, Data & ML Engineering

Location:

US (Remote) Interested applicants must reside in one of the following approved states:
Arizona, California, Colorado, Indiana, Massachusetts, Minnesota, New York, Oregon, Pennsylvania, Texas, Utah, Washington

As the Data Engineering Lead, you will be the senior technical voice within Deckers’ data and ML engineering organization. You’ll provide hands‑on leadership for data engineering design, build quality, and delivery standards across our enterprise data products. This role is all about setting the bar for technical excellence—establishing design patterns, coding standards, and review gates for distributed engineering teams, including external partners.

You’ll build engineering capability through design review, pairing, coaching, and structured knowledge transfer, ensuring our data products are reliable, scalable, and ready to power business decisions. 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.

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 build begins on significant work. Own engineering standards for model design and naming, code review, CI/CD, 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 the technical quality of their output to Deckers standards. Coach and develop data engineers and analytics engineers through design review, pairing, technical guidance, and structured knowledge transfer.

Reduce key‑person dependency by documenting engineering patterns, designs, and runbooks so that critical knowledge is retained by the organization. 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.

• Bachelor’s degree required, preferably in Computer Science, Computer Engineering, or a related technical field;
  Master’s…