Analytics Engineer - Remote

BaubleBar is seeking an Analytics Engineer to build and maintain the data foundation that supports reporting and decision-making across the organization. The role focuses on developing reliable data models, supporting data quality and business intelligence, and partnering with stakeholders on analytics needs.

Responsibilities:

• 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
• 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
• 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
• 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

Requirements:

• 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
• Position will be remote (residing anywhere in the United States and authorized to work in the U.S.)
• Bachelor's degree in Analytics, Data Science, Computer Science, Information Systems, Mathematics, or a related quantitative field preferred
• equivalent relevant professional experience
• 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