Director of Data Engineering

This is a senior data leadership role responsible for building and scaling the data foundation that powers critical business decisions. You'll own the data roadmap, architecture, and company-wide data model while creating a trusted single source of truth for core business information.

• Own the data roadmap, architecture, and company-wide data model, establishing a trusted single source of truth for core business data.
• Modernize and refactor legacy data jobs, reducing technical debt and creating a platform that can scale with business growth.
• Ensure data pipelines remain resilient, reliable, accurate, and consistently available to teams across the organization.
• Establish and maintain strong data quality, governance, monitoring, and observability practices.
• Manage warehouse and infrastructure costs as data volumes and business requirements increase.
• Lead the team's intake and sprint-planning process, prioritizing requests according to business impact while adapting to changing priorities.
• Lead, coach, and develop a small data engineering team through code reviews, regular feedback, mentorship, and clear growth paths.
• Stay hands-on with technical work when required, contributing directly to architecture, engineering, troubleshooting, and platform improvements.
• Integrate new enterprise systems, including ERP platforms, into the data warehouse and broader data ecosystem.
• Introduce and scale AI-native ways of working, using AI agents for software development, incident investigation, data quality, and engineering productivity.
• Promote a pragmatic engineering approach that starts with the business question and selects the simplest technology capable of solving it.
• Foster a culture where data integrity and trust are treated as critical, priorities are managed decisively, and engineers are supported in developing into senior contributors and future managers.

• 8+ years of experience in data architecture or data engineering, including at least 3 years of experience leading teams.
• Proven experience building and scaling cloud-based data platforms, with BigQuery or a comparable technology.
• Strong hands-on expertise in SQL and Python, along with dbt or a similar data modeling framework.
• Deep experience with data modeling and the ability to design data structures starting from business concepts and requirements rather than simply from existing tables.
• Experience establishing data quality, governance, monitoring, and observability practices that create confidence across the organization.
• Experience managing sprint-based intake, prioritization, and delivery for a data team supporting multiple business stakeholders.
• Familiarity with ELT platforms such as Fivetran and comparable data integration tools.
• Experience working with enterprise systems and data integrations; ERP experience is a plus.
• Experience in direct-to-consumer (DTC) or consumer packaged goods (CPG) environments is preferred.
• Strong judgment and prioritization skills, with the ability to balance urgent business needs against long-term platform health and technical debt.
• Hands-on leadership style with the ability to move between strategic planning, technical problem-solving, and people management.
• Strong coaching and communication skills, with a commitment to developing engineers and creating clear paths for professional growth.
• Practical experience using AI agents or AI-assisted engineering tools, with an openness to making AI a meaningful part of day-to-day technical workflows.

• Base salary of $200,000 plus bonus and incentive compensation, depending on experience.
• Comprehensive benefits package supporting employee and family well-being.
• Strong healthcare benefits coverage.
• Generous paid time off.
• Wellness and health-focused perks.
• Free access to company products.
• Fully remote, high-trust working environment.
• Biannual company off-sites providing opportunities for in-person connection and collaboration.
• Significant ownership and influence over the organization's data strategy and technical foundation.
• Opportunities for career growth and meaningful impact while building an enterprise-level data function.