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Data Engineer (Looker)

Dice
Raleigh, NC, US Posted Oct 6, 2026
Hybrid

About this role

Data Engineer (Looker)

Raleigh, NC, US • Posted 8 hours ago • Updated 8 hours ago

Full Time

Able to Sponsor

On-site

Depends on Experience

Fitment

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Job Details

Skills

  • LookML

  • Looker

  • Warehouse Management Systems

  • WMS

  • Summary

  • Job Title: Data Engineer (Looker)

  • Work

Location

Raleigh, NC (Hybrid)

Long Term Contract

NOTE : Only local candidate is Required

If you find this opportunity suitable, kindly share your updated resume. Also, please let me know a good time to connect with you for a quick discussion.

Looking forward to hearing from you!

Job Description

Looking for Data Engineer with strong LookML and Looker development expertise Data Modeling & LookML Development, Design, develop, and maintain LookML models, views, explores, and dashboards within the Looker platform. Implement reusable semantic data layers to support self-service analytics. Create optimized data models for automotive parts inventory, sales performance, supplier management, and logistics reporting. Develop dimensions, measures, derived tables, PDTs, and LookML best practices. Data Engineering background Design and develop scalable ETL/ELT pipelines. Integrate data from ERP, Warehouse Management Systems (WMS), Supply Chain systems, and third-party sources. Perform data transformation using SQL, Python, DBT, or cloud-native tools. Must have data quality, lineage, governance, and performance optimization. 5+ years of Data Engineering experience. 5+ minimum experience in Azure/AWS Google 3+ years of Looker / LookML Development experience. Advanced SQL programming. Data Modeling and Data Warehousing concepts. Experience building semantic layers and analytical models. ETL/ELT development experience. Strong understanding of dimensional modeling (Star/Snowflake Schema). Git version control experience. Must have Google Cloud Platform:

  • Experience with CI/CD pipeline management in DevOps
  • Good to have DBT, Python, PySpark, Snowflake and Databricks

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