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WHAT WE OFFER: 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!Read the full posting
- 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.)
From the employer’s posting.
BaubleBar designs accessories that make life more fun.
In the employer’s words · Read in context
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Day 14
Similar jobs usually come down between day 6 and day 47.
From 1,405 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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
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
- 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
- Evaluate upstream and downstream dependencies before modifying existing models - Follow established SQL, dbt, documentation, and version-control standards Data Quality & Troubleshooting
WHAT WE WANT TO SEE: 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.
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. Candidates should also have:
- 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
Experience with any of the following is helpful, but not required: - dbt or another SQL-based data transformation framework - Snowflake, BigQuery, Redshift, Databricks, or another modern cloud data platform
- 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
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. WHAT WE WANT YOU TO DO:
- 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
- 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
- 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
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
WHO WE ARE:
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.
WHAT WE'RE LOOKING FOR:
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.
WHAT WE WANT YOU TO DO:
Data Modeling & Analytics Engineering
Development & Version Control
Data Quality & Troubleshooting
Business Intelligence & Business Partnership
WHAT WE WANT TO SEE:
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.
Candidates should also have:
Experience with any of the following is helpful, but not required:
WHAT WE OFFER:
Selected passages from the saved posting. Check the full description for conditions and exceptions.
WHAT WE OFFER: 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!
Anywhere
- 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.) Experience with any of the following is helpful, but not required:
- 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.) Experience with any of the following is helpful, but not required: