BaubleBar designs accessories that make life more fun. Founded in 2010, the Company is known for its statement-making styles that create joy and bring people together. Today, BaubleBar’s unabashedly optimistic perspective can be found across multiple accessory categories that are sold direct to consumer and at 8,500+ retail stores globally.

We are seeking an Analytics Engineer to join our Data Analytics team and help build and maintain the data foundation that supports reporting and decision-making across the organization.

This is a hands-on, early-to-mid-career role for someone with an excellent foundation in SQL, data modeling, and modern analytics engineering practices. The Analytics Engineer will work closely with analytics leadership to translate business requirements into reliable, scalable data models while developing deeper technical and business expertise.

Our current data stack includes Fivetran, dbt, GitHub, Snowflake, and Power BI. Experience with our exact technology stack is not required. Strong technical fundamentals, sound data-modeling instincts, and the ability to learn quickly are more important than experience with a particular platform.

Data Modeling & Analytics Engineering

• Write clean, efficient, and maintainable SQL to transform raw business data into reliable, analytics-ready datasets
• Develop and maintain staging, intermediate, dimensional, fact, and reporting-layer data models
• Translate business requirements and established architecture into production data models
• Apply dimensional modeling concepts with a strong understanding of grain, relationships, and dependencies
• Refactor and improve existing SQL and data models as business requirements evolve
• Enhance existing data models for self-service and AI-powered analytics by improving metadata, descriptions, and semantic context for tools such as Snowflake Cortex AI
• Build and maintain data-quality tests and documentation

Development & Version Control

• Use Git and GitHub to manage analytics code through branches, commits, pull requests, code reviews, and deployment workflows
• Develop and test changes before deploying them to production
• Evaluate upstream and downstream dependencies before modifying existing models
• Follow established SQL, dbt, documentation, and version-control standards

Data Quality & Troubleshooting

• Investigate data-quality issues and discrepancies between reporting and source systems
• Trace data through source, transformation, and reporting layers to identify root causes
• Troubleshoot failed transformations and scheduled analytics jobs
• Validate changes and develop sustainable solutions rather than relying on manual fixes or workarounds

Business Intelligence & Business Partnership

• Support the data and semantic models used for business intelligence and self-service analytics
• Partner with business stakeholders to understand reporting needs and determine the appropriate underlying data structure
• Help maintain consistent definitions and calculations for key business metrics
• Develop an understanding of key business processes across E-Commerce, Wholesale, Merchandising, Marketing, Supply Chain, Operations, and Finance

Excellent SQL skills are the most important technical qualifications for this position.

You should be comfortable working with complex SQL involving joins, CTEs, aggregations, window functions, conditional logic, and multi-step transformations. Just as importantly, you should understand what your SQL is doing to the underlying data and be able to reason about grain, relationships, cardinality, duplication, nulls, and unexpected results.

• Approximately 2-4 years of relevant experience in analytics engineering, data analytics, business intelligence, data engineering, or a related field
• Strong understanding of relational data and data modeling concepts
• Experience transforming operational data into structured datasets used for analytics and reporting
• Practical experience using Git for version control and collaborative development
• Experience working with a SQL-based cloud data warehouse or relational database
• Strong analytical and troubleshooting skills with the ability to break complex data problems into logical, testable steps
• Strong attention to detail and commitment to data accuracy
• Curiosity about how business processes generate and affect data
• Ability to learn unfamiliar technologies and business domains quickly
• Bachelor's degree in Analytics, Data Science, Computer Science, Information Systems, Mathematics, or a related quantitative field preferred, or equivalent relevant professional experience
• Position will be remote (residing anywhere in the United States and authorized to work in the U.S.)

• dbt or another SQL-based data transformation framework
• Snowflake, BigQuery, Redshift, Databricks, or another modern cloud data platform
• Power BI, Sigma, Tableau, Looker, or another BI platform
• Fivetran or another ELT/data integration platform
• Python, APIs, SFTP/file-based integrations, or semi-structured data
• Retail, e-commerce, wholesale, inventory, supply chain, or financial data
• NetSuite, Shopify, Amazon, Klaviyo, or similar business platforms

• Starting salary range for this role is $105,000-$115,000. Starting offer within that range will factor in work location, skills, background and years of relevant experience
• Generous benefit package including: Outstanding company contribution towards employee premiums for Medical, Dental and Vision Insurance, PTO, 10 paid Company Holidays, Company paid Life Insurance & more!
• Company laptop, free monthly product allowance and employee discounts