Data and Analytics Engineer at Burlebo – Austin, Texas

BURLEBO is a growing brand in men's outdoor clothing, dedicated to providing high-quality, durable, and stylish gear for the Athlete, the Outdoors, and the Family. We are passionate about innovation, sustainability, and performance-driven apparel that empowers our team and customers to explore the great outdoors with confidence.

Role: Lead Data & Analytics Engineer
Overview
We’re looking for an experienced, proactive data professional to build and lead our data and analytics function from the ground up.
We have a growing data environment in GCP (BigQuery, Cloud SQL) across ecommerce, wholesale, and fulfillment systems (Shopify, ShipHero, NuOrder, etc.).
This is a foundational role. You will be the first dedicated data hire, responsible for bringing structure to our data, defining how we use it, and helping the company make better decisions.
You’ll work directly with leadership and collaborate with a small technical team, while also mentoring junior team members who will support analytics efforts over time.
Over time, this role is expected to grow into leading data team as the company scales.
This is a hands-on role for someone who enjoys both building systems and developing people.

**MUST BE ABLE TO WORK IN OFFICE: AUSTIN HQ**

**ATTENTION: To be considered for position, YOU MUST fill out this survey.**
https://go.cultureindex.com/p/PHBamIPqKwUaH

What You’ll Do
Build the Data Foundation

• Own and improve our data environment in GCP (BigQuery, Cloud SQL)
• Structure and model data across ecommerce, wholesale, and fulfillment systems
• Define core company metrics and ensure consistency across teams
• Identify and resolve data discrepancies across systems

Own Analytics & Reporting

• Design and build dashboards used by leadership and operations
• Establish standardized reporting across departments
• Replace ad-hoc spreadsheet workflows with scalable solutions
• Ensure data is accessible and understandable across the company

Drive Business Insights

• Partner with leadership to define what we should measure and why
• Analyze product performance, inventory trends, and customer behavior
• Proactively surface insights that impact revenue, operations, and efficiency

Build & Develop the Data Function

• Act as the owner of data and analytics within the company
• Mentor and guide junior team members supporting analytics work
• Establish best practices for data modeling, reporting, and governance
• Help define the roadmap and structure for the future data team
• Contribute to hiring and scaling the team over time

What We’re Looking For

• 4–8+ years of experience in data analytics, analytics engineering, or similar roles
• Strong SQL skills and experience with modern data warehouses (BigQuery preferred)
• Experience building and owning dashboards used by business stakeholders
• Experience working in environments with messy or evolving data
• Proven ability to work independently and bring structure to ambiguity
• Strong communication skills — able to translate data into business insights
• Experience mentoring or guiding others (formal or informal)

Nice to Have (Not Required)

• Experience in ecommerce or retail (Shopify, inventory, order data, etc.)
• Familiarity with GCP (BigQuery, Cloud SQL)
• Experience with dbt or data modeling frameworks
• Basic Python for analysis or automation
• Experience working across multiple operational systems (WMS, ERP, etc.)

What Success Looks Like
Within 6–12 months:

• Core company metrics are clearly defined and trusted across teams
• Data discrepancies across systems are identified and significantly reduced
• Leadership has reliable dashboards for key decisions
• Reporting is standardized and scalable (not ad-hoc)
• Junior team members are contributing effectively under your guidance
• A clear roadmap exists for how the data function will scale with the business

Growth Opportunity
This role is designed to evolve into a senior leadership position within the company.
As we scale, this person will have the opportunity to:

• Build and lead a dedicated data team
• Shape the company’s data strategy
• Influence key decisions across operations, merchandising, and growth
• Grow into a long-term leader within the technology organization