Data Engineer

We’re hiring a Data Engineer to build and evolve the data foundation that powers insights across the business. You’ll be the bridge between our data infrastructure and our business users - designing, developing, and maintaining the systems that make high-quality data accessible, reliable, and actionable. This is an engineering-heavy role, focused on building and optimizing our data pipelines, models, and automations. But it’s also a role that requires genuine curiosity about how the business works and the ability to communicate clearly with people who don’t speak SQL.

You’ll serve as the principal technical owner of our data stack - Snowflake, Fivetran, dbt, Census, and Sigma - and provide technical leadership to our analysts, analytics engineers, and engineering contractors. You’ll partner directly with teams across Marketing, Operations, Finance, and Product to understand their data needs and build solutions they actually trust and use.

If you love building data systems that make smart people smarter - and you also love working in a non-traditional, eclectic, irreverent environment - keep reading., Data Modeling & Infrastructure

• Design, build, and maintain data models in Snowflake serving analytics, reporting, and operational use cases for both human and AI consumers
• Manage and optimize data pipelines to move data reliably between operational and analytics applications
• Own data orchestration, observability, and quality management - ensuring robust monitoring and alerting are in place
• Partner with data and systems teams to improve automation, data integrity, and pipeline reliability

Business Partnership & Translation

• Collaborate with business and analytics teams to understand their needs and translate them into scalable data solutions
• Occasionally assist with data analysis to guide key business decisions
• Build trust and transparency around data across all teams through clear communication and documentation

AI Connectivity & Emerging Use Cases

• Enable and support AI connectivity and reliable, trusted use of our data models
• Leverage AI coding tools (Cursor, Claude Code, GitHub Copilot, or similar) to increase productivity and product quality in production
• Stay ahead of emerging patterns in AI-augmented analytics and bring forward recommendations for how GLDN can benefit

Technical Leadership

• Serve as principal technical owner of the data stack: Snowflake, Fivetran, dbt, Census, and Sigma
• Provide technical leadership and mentorship to analysts, analytics engineers, and engineering contractors
• Set and enforce standards for data governance, master data management, and documentation
• Drive continuous improvement of the data platform to support GLDN’s growth, Month 1: Get deep on the current data stack, existing pipelines, and data model structure. Work closely with the existing data team to understand business priorities and how our current data products support them. Get to know key stakeholders across the business.

Month 2: Start building production pipelines and data models. Recommend improvements to current pipelines as you find them. Help guide innovative solutions to support GLDN’s strategic priorities.

Month 3: Take over ownership of entire end-to-end stack. Take on all observability and orchestration responsibilities. Shift from supporting current data engineering lead (part time contractor) to being supported by them.

SUCCESS METRICS (FIRST 12-18 MONTHS)

• Data quality and reliability issues identified and fixed before business users find them
• Data efforts support GLDN initiatives that deliver at least 3x the data investments
• At least one impactful AI-connected data use case shipped and in production, with clear monitoring of reliability and accuracy

WHAT YOU’LL GAIN

• Ownership over the data foundation of a growing DTC brand - the kind of greenfield opportunity that’s rare at this company stage
• A direct line to business impact: the work you build is used by every team in the company
• The chance to build AI-connected data infrastructure from the ground up
• A collaborative, low-ego team that values craft and clear thinking, Written responses to all five questions below (there are no wrong answers - we’re looking for how you think):
• Describe a data model or pipeline you built that had a measurable impact on a business decision. How did you identify the need, and how did you know it was successful?
• Describe a time a major data pipeline you owned failed in production. How did you detect it, resolve it, and prevent recurrence? How did you manage stakeholders during the resolution process?
• What’s a data governance or master data management challenge you’ve encountered, and how did you approach solving it without slowing the business down?
• Have you designed or maintained data models for consumption by AI systems (e.g., LLMs, agents)? How does that change your modeling decisions compared to building for human analysts?
• We are a small team and often have to help each other out. Are you comfortable flexing into lightweight data analysis, data science, or product management roles from time to time as projects require?

Do you have experience in Vendor contract management?, Required

• 5+ years of experience in data engineering, or a related role
• Strong proficiency in SQL, Python, and modern data modeling practices
• Hands-on experience with our core stack: Snowflake, Fivetran, dbt, Census, and Sigma
• Demonstrated use of AI coding tools (Cursor, Claude Code, GitHub Copilot, or similar) in a production environment
• Demonstrated ability to collaborate directly with business users and communicate clearly with both technical and non-technical audiences

Preferred

• Experience with ecommerce data structures and integrations (Shopify, Klaviyo, Google Analytics, etc.)
• Experience with manufacturing and warehouse management data; Odoo ERP experience a plus
• Familiarity with data orchestration and observability tools
• Experience with AWS or equivalent cloud services
• Experience with data governance and master data management tools, * Systems thinking: able to design for reliability, scale, and maintainability from the start
• Strong analytical and problem-solving ability
• Ability to translate complex technical concepts into language business users understand
• Self-starter who can manage multiple priorities and deliver with high reliability and transparency
• Balances speed and precision - knows when “good enough” is good enough
• Values clear communication: documentation, updates, and cross-functional collaboration

5.05.0 out of 5 stars Remote $108,000 - $140,000 a year - Full-time, Pulled from the full job description

• Parental leave
• 401(k)
• Health insurance
• Paid time off
• Employee discount
• Vision insurance
• Health savings account, * 401(k)
• Dental insurance
• Employee assistance program
• Employee discount
• Flexible schedule
• Health insurance
• Health savings account
• Paid time off
• Parental leave
• Vision insurance

GLDN is a direct-to-consumer jewelry brand that blends craft and technology to bring delight and connection through meaningful, personalized pieces. We design, manufacture, and ship from our headquarters in La Conner, Washington, with 20,000+ SKUs spanning made-to-order and in-stock products. We are growing - and the data infrastructure that powers decisions across marketing, ecommerce, manufacturing, and fulfillment needs to grow with us.