Director Shopify Engineering Jobs (NOW HIRING)

HELP BUILD THE DATA FOUNDATION THAT POWERS SMARTER DECISIONS.

POLYWOOD® is looking for a Director of Data Engineering who thrives in a hands-on leadership environment and enjoys building scalable enterprise data platforms. This role is perfect for someone who loves designing architecture, establishing governance, and transforming raw ingestion pipelines into a structured, reliable Databricks lakehouse that powers enterprise reporting, operational analytics, and Direct-to-Consumer performance measurement.

What You’ll Do:

• Design and implement a scalable lakehouse medallion architecture within Databricks.

• Establish ingestion, canonical, and business-ready data modeling layers with clear standards and naming conventions.

• Build and maintain structured, governed fact and dimension models for enterprise reporting.

• Oversee ingestion pipelines using Fivetran, Airbyte, and custom integrations while optimizing cost and performance.

• Develop and manage SQL and Python transformation jobs including incremental processing, upsert logic, and snapshot modeling.

• Implement orchestration, monitoring, data quality validation, and failure recovery processes.

• Define enterprise data governance standards including access controls and reconciliation processes.

• Integrate ERP, Shopify, GA4, Google Ads, Meta Ads, and catalog marketing data into unified customer and order models.

• Lead and mentor a small team of data and analytics engineers while setting coding and review standards.

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What You Bring:

• 7+ years of experience in data engineering, analytics engineering, or data architecture.

• 3+ years leading data platform or warehouse initiatives.

• Expert-level expertise in Databricks and medallion architecture design.

• Advanced SQL proficiency and strong Python experience for data transformations.

• Experience designing fact/dimension models and implementing incremental pipelines and snapshot logic.

• Strong understanding of data governance, access control, and quality frameworks.

• Experience integrating commerce, finance, ERP, and marketing data sources into structured models.

• Strong communication skills and the ability to collaborate across technical and business teams.

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Bonus Skills:

• Experience with Direct-to-Consumer and commerce analytics environments.

• Experience optimizing pipeline cost and performance within cloud data platforms.

• Experience formalizing enterprise metric definitions across finance and operations.

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Why You’ll Love Working With Us:

• Valued Contribution: Build the foundational data infrastructure that powers enterprise decisions.

• Growth Opportunities: Shape standards, architecture, and long-term data strategy.

• Team Environment: Partner with business leaders and analytics teams to deliver trusted insights.

• Purpose Driven Work: Enable scalable analytics that strengthen operations, finance, and commerce performance.

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 About Us

At POLYWOOD®, we design and build outdoor furniture that brings people together and stands the test of time. We do this using sustainable materials like our genuine POLYWOOD® lumber made from recycled plastics. But the strength of our products starts with the strength of our systems and our people.
This role plays an important part in operationalizing our Databricks investment by building a cohesive, governed, and scalable enterprise data warehouse. By establishing reliable ingestion, transformation, and modeling standards, you help ensure our organization can make confident, data-driven decisions at scale.

 Check out this video - Genuine Polywood  
If this sounds like the kind of impact you want to make, we’d love to meet you! Apply today!

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POLYWOOD is an equal opportunity employer. POLYWOOD evaluates qualified applicants without regard to characteristics protected by federal, state, or local laws. #ZR

Notice of AI Use in Job Application Review

As part of our commitment in creating a fair, efficient, and consistent hiring process we may use artificial intelligence (AI) to help our recruiting teams organize, summarize, and analyze information provided by candidates, including resumes, application responses, and other materials submitted during the application process.AI may be used to identify patterns, highlight relevant skills, and experience, and assist in comparing a candidate’s qualifications with the requirement of a specific role. These tools are to improve efficiency and consistency while supporting more informed hiring decisions, which will ultimately be made by the hiring team.