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Salary: USD 105,000 - 115,000 / annual
BaubleBar is seeking an Analytics Engineer to join its Data Analytics team and build the data foundation supporting reporting and decision-making across the organization. This is a hands-on, early-to-mid-career role focused on translating business requirements into reliable, scalable data models using modern analytics engineering practices.
You will work closely with analytics leadership on data modeling and transformation, using a current tech stack of Fivetran, dbt, GitHub, Snowflake, and Power BI. Strong technical fundamentals and sound data-modeling instincts are prioritized over specific platform experience.
Key responsibilities include:
**Data Modeling & Analytics Engineering:** Write clean, efficient SQL to transform raw business data into analytics-ready datasets. Develop and maintain staging, intermediate, dimensional, fact, and reporting-layer data models. Translate business requirements into production models using dimensional modeling concepts. Refactor existing SQL and models as requirements evolve. Enhance data models for self-service and AI-powered analytics by improving metadata and semantic context. 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 production deployment. Evaluate upstream and downstream dependencies before modifying 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 jobs. Validate changes and develop sustainable solutions.
**Business Intelligence & Partnership:** Support data and semantic models for business intelligence and self-service analytics. Partner with business stakeholders to understand reporting needs and determine appropriate data structures. Maintain consistent definitions and calculations for key business metrics. Develop understanding of key business processes across E-Commerce, Wholesale, Merchandising, Marketing, Supply Chain, Operations, and Finance.
BaubleBar designs accessories sold direct-to-consumer and at 8,500+ retail stores globally, founded in 2010.
**Requirements:**
- Approximately 2–4 years of relevant experience in analytics engineering, data analytics, business intelligence, data engineering, or related field
- Excellent SQL skills (most important qualification): comfortable with complex SQL involving joins, CTEs, aggregations, window functions, conditional logic, and multi-step transformations; ability to reason about grain, relationships, cardinality, duplication, nulls, and unexpected results
- Strong understanding of relational data and data modeling concepts
- Experience transforming operational data into structured datasets for analytics and reporting
- Practical experience using Git for version control and collaborative development
- Experience with SQL-based cloud data warehouse or relational database
- Strong analytical and troubleshooting skills; 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 related quantitative field preferred, or equivalent relevant professional experience
- Must be authorized to work in the U.S.
**Helpful (not required):** dbt or other SQL-based data transformation frameworks; Snowflake, BigQuery, Redshift, Databricks, or other modern cloud data platforms; Power BI, Sigma, Tableau, Looker, or other BI platforms; Fivetran or other ELT/data integration platforms; 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.
