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# BI Developer - Data Architecture

- **Company:** Dexian DISYS
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $120,000.0 - $125,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Data Governance, Extract Transform Load (ETL), Data Warehousing, Netsuite, Performance Tuning, Shopify, Freeform SQL, Sql Optimization, Snowflake, Data Lineage, Looker Analytics
- **Published:** July 29, 2026
- **Apply:** https://www.dice.com/job-detail/a887874b-57d6-4415-a0c2-3cee1a6c0b1d

## About the Role

* 5+ years of experience as a BI Developer, Analytics Engineer, or similar role.
 * Strong hands-on experience with Snowflake and advanced SQL.
 * Experience developing LookML models and working with Looker.
 * Strong understanding of data modeling, data warehousing, and ETL/ELT processes.
 * Experience with retail or eCommerce data, preferably working with platforms such as Shopify, NetSuite, or similar ERP/eCommerce systems.
 * Knowledge of data governance, data quality, and documentation best practices.
 * Excellent communication skills with the ability to work directly with both technical and business stakeholders.

## Description

I'm working with a growing retail/eCommerce company that's investing in its modern data platform and looking to hire a Senior BI Developer. This is a hands-on technical role focused on building and optimizing the company's BI and analytics environment. The ideal candidate will have strong experience with Snowflake, Looker/LookML, and advanced SQL and enjoy solving complex data challenges., * Design, develop, and optimize data models and transformation logic in Snowflake.

 * Build and maintain LookML models, Explores, and semantic layers in Looker.
 * Write and optimize complex SQL queries to improve data quality and performance.
 * Develop and support ETL/ELT processes to ensure accurate and reliable data.
 * Partner with Finance, Operations, Marketing, and other business teams to translate reporting requirements into scalable data solutions.
 * Establish and maintain data governance, documentation, and data lineage.
 * Monitor data quality, troubleshoot pipeline issues, and support new data source integrations.
 * Continuously improve the BI platform by identifying opportunities for automation and performance optimization.


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