Analytics Engineer - Remote
宝贝巴尔公司在全球范围内销售直接给消费者和8500多家零售商店的多个配件类别中可以找到无耻乐观的观点。我们正在寻找一个分析工程师加入我们的数据分析团队,帮助建立和维护组织中支持报告和决策的数据基础。这是一个实用,早期到中期职业生涯的角色,对于一个拥有 SQL,数据建模和现代分析工程实践的优秀基础的人来说。分析工程师将与分析领导层密切合作,将业务要求转化为可靠,可扩展的数据模型,同时开发更深入的技术和商业专业知识。我们的当前数据堆包括 Fivetran,dbt,GitHub,Snowflake 和 Power BI.我们精确的技术堆积体验不需要。强大的技术基本面,健全的数据建模本能以及快速学习的能力比特定平台的经验更重要。我们要做什么:数据建模与分析工程 · 写清洁,高效和可维护的 SQL 以将原始业务数据转化为可靠的,准备好进行分析的数据集 · 在业务需求不断发展时开发和维护阶段性,中级,尺寸性,事实性和报告层数据模型 · 将业务要求和建立的架构转换成生产数据模型 · 用于对谷物,关系和依赖性的强大理解而应用维度建模概念 · 随着业务需求的演变,重新构想并改进现有 SQL 和数据模型 ·通过改善如 Snowflake Cortex AI 等工具的元数据,描述和语义背景来提高自动服务和人工智能驱动分析的现有数据模型 · 建立并维护数据质量测试和文档开发与版本控制 · 使用 Git 和 GitHub 以管理通过分支机构进行分析代码,提交,拉引请求,代码审查和部署工作流程 · 在部署到生产之前制定和测试变化 · 在修改现有的模型前评估上下游依赖性 ·遵循已建立的 SQL 标准,dbt,文档和版本控制数据质量和故障解决 ·调查数据质量问题和报告与数据的差异
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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
- 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
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:
- 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.)
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
- 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
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!
- Company laptop, free monthly product allowance and employee discounts
Originally posted on Himalayas