Analytics Engineer (Business Intelligence)

About Nuqleous Nuqleous is a leading developer of intelligent technology solutions that enable retailers and consumer product companies to operate with enhanced agility and efficiency. Nuqleous - Total Rewards builds data and analytics platforms that helps Walmart turn complex operational data into reliable insights and scalable decision-making systems. Our teams partner closely with Walmart to design and operate modern data platforms built on technologies like Snowflake, dbt, and cloud infrastructure. We focus on building clean, validated datasets, scalable data models, and reliable reporting layers that business teams can trust for planning, forecasting, and operational decision-making. As we continue to grow, we are investing in modern data engineering practices, strong data quality frameworks, and scalable analytics architectures that support long-term client partnerships. Joining Nuqleous means working on real enterprise problems where well-designed data systems directly impact business operations and decision making.

About the Role

We're looking for a hands-on Analytics Engineer to help build and scale the data models and reporting layer supporting one of our largest enterprise client engagements. In this role, you’ll work closely with our Lead Analyst to transform raw data into well-structured, analytics-ready datasets and reporting solutions. You’ll translate analytical requirements and prototypes into reliable dbt models, Snowflake schemas, and business intelligence assets used by both internal teams and customers. This role is ideal for someone who enjoys building clean, maintainable data systems and wants to grow in a collaborative environment where data and analytics directly influence product development and business decisions.

What You Will Do

• Build and maintain dbt models that transform raw data into clean, analytics-ready datasets in Snowflake
• Design and manage Snowflake schemas that support reporting and analytical use cases
• Develop and maintain semantic models, reports, and dashboards in MicroStrategy
• Work closely with the Lead Analyst to translate requirements and analytical prototypes into production-ready data models and reporting solutions
• Troubleshoot data quality issues and ensure pipelines and reporting assets remain reliable and performant
• Improve the consistency, documentation, and maintainability of our data models and analytics assets
• Contribute to the ongoing improvement of our data modeling practices and analytics workflows

Requirements

What We are Looking For

• Experience building and maintaining dbt models that transform raw data into analytics-ready datasets
• Strong working knowledge of Snowflake, including schema design, query optimization, and warehouse management
• Experience developing reports and dashboards in a BI platform such as MicroStrategy, Tableau, Looker, Power BI, or similar
• Familiarity with semantic or schema layer concepts such as metrics, attributes, hierarchies, and dimensional modeling
• Ability to translate analytical requirements or prototypes into clean, scalable data models and reporting solutions
• Strong attention to detail and a commitment to data accuracy and reliability
• Experience identifying and troubleshooting data quality issues
• Comfort collaborating with analysts and stakeholders to clarify requirements and iterate on solutions
• Clear communicator who can surface blockers early and ask thoughtful questions

What Success Looks Like in the First 90 Days First 30 Days

• Become familiar with our data stack, analytics workflows, and core datasets
• Understand how our analytics models and reporting support both internal teams and customers
• Begin contributing improvements or small enhancements to existing dbt models and reports

Days 30–60

• Build and maintain dbt models that support new analytics and reporting needs
• Translate analytical prototypes or requirements into production-ready models and reports
• Improve documentation and consistency across our data models and reporting assets

Days 60–90

• Independently deliver new analytics models and reporting features
• Help improve the reliability and maintainability of key datasets used by the analytics team
• Contribute ideas for improving our data modeling patterns and analytics workflows

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