VP of Data & Analytics

Job Description

Job Description

Description:

 

POLYWOOD | Hybrid / Remote | Reports To: Chief Digital Officer

The Opportunity

POLYWOOD is building something most companies talk about but few actually achieve: a data organization that doesn't just report on the business but shapes it. We're evolving from outdoor furniture to outdoor living, and the decisions that drive that shift need to be grounded in real consumer insight, commercial intelligence, and operational clarity.

This is the role that makes that happen.

The Role

The VP of Data & Analytics is POLYWOOD's senior data leader, responsible for the people, platforms, and practices that turn raw data into business advantage. You'll own the enterprise data platform, lead a team of data and analytics engineers, and manage embedded analysts across the organization who sit close to the business units they serve.

Critically, this role isn't just internal infrastructure. You'll be a key partner to Marketing, Advertising, and Commercial leadership, ensuring that data drives smarter decisions across the consumer journey, from acquisition to retention to repurchase.

You'll lead the organization through two direct reports:

• Director of Data Engineering who builds and maintains the data platform and pipelines
• Embedded Analysts across business units who translate data into action at the point of need

What You'll Own Data Strategy and Platform Leadership

• Define and evolve POLYWOOD's enterprise data strategy, from ingestion to insight
• Own the Databricks lakehouse environment and ensure it's structured, governed, and built for scale
• Set the architectural standards, modeling conventions, and data quality frameworks that the whole organization relies on
• Stay technically credible: you understand medallion architecture, transformation pipelines, and data modeling well enough to lead a Director of Data Engineering and make sound platform decisions

Analytics and Organizational Leadership

• Lead and develop a team of data engineers, analytics engineers, and embedded business analysts
• Ensure embedded analysts are well-connected to both their business units and to the central data org, so insights are consistent, reliable, and actually used
• Build a culture of curiosity, rigor, and practical impact across the team
• Partner with HR and business unit leaders to grow the analyst function as the company scales

Commercial and Marketing Partnership

• Serve as the primary data partner to Marketing, Advertising, and Commercial leadership
• Ensure consumer and marketing data pipelines, including Shopify, GA4, Google Ads, and Meta, are structured to support attribution, performance measurement, and audience intelligence
• Connect data to commercial decisions: pricing, assortment, promotions, and customer lifecycle
• Help define the KPIs and measurement frameworks that align creative, media, and business teams around shared outcomes

Governance and Data Quality

• Establish and enforce data governance standards, access controls, and metric definitions across the organization
• Ensure finance and operations are working from the same numbers
• Reduce reliance on manual reporting and ad hoc data pulls by building reliable, self-serve business-ready models

What We're Looking For

• Technical Leader who is credible with engineers and can make sound architectural decisions, not just manage up
• Organizational Builder who knows how to structure a data org, develop talent, and connect embedded analysts to a central platform
• Commercial Partner who understands how data connects to marketing performance, consumer behavior, and business outcomes
• Clear Communicator who can translate technical complexity into business decisions at the executive level

Qualifications

• 12+ years in data engineering, analytics, or data leadership roles
• Significant experience leading multi-disciplinary data organizations including engineers and analysts
• Expert-level knowledge of Databricks and modern lakehouse architecture
• Strong SQL and Python fluency; ability to review and guide technical work
• Experience integrating D2C and marketing data sources (Shopify, GA4, paid media platforms)
• Proven ability to connect data strategy to measurable business outcomes
• Experience in consumer products, retail, or D2C environments preferred

Why POLYWOOD

You'll be building the data foundation for a category-defining brand at a moment of real strategic ambition. The platform is in place. The business appetite is there. This is a chance to build something that actually matters.

Requirements:

 

What We're Looking For

• Technical Leader who is credible with engineers and can make sound architectural decisions, not just manage up
• Organizational Builder who knows how to structure a data org, develop talent, and connect embedded analysts to a central platform
• Commercial Partner who understands how data connects to marketing performance, consumer behavior, and business outcomes
• Clear Communicator who can translate technical complexity into business decisions at the executive level

Qualifications

• 12+ years in data engineering, analytics, or data leadership roles
• Significant experience leading multi-disciplinary data organizations including engineers and analysts
• Expert-level knowledge of Databricks and modern lakehouse architecture
• Strong SQL and Python fluency; ability to review and guide technical work
• Experience integrating D2C and marketing data sources (Shopify, GA4, paid media platforms)
• Proven ability to connect data strategy to measurable business outcomes
• Experience in consumer products, retail, or D2C environments preferred

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.