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Data Engineer

Data Engineer

Jaipur RugsNagpur, IN
10 hours ago
Job description

Organization Description : Jaipur Rugs is a social enterprise that connects rural craftsmanship with global markets through its luxurious handmade carpets. It is a family-run business that offers an exclusive range of hand-knotted and hand-woven rugs made using 2500 years old traditional art forms. The founder, Mr. Nand Kishore Chaudhary created a unique business model, which provides livelihood to the artisans at their doorstep. This changed the standard practice of involving middlemen to work with artisanal communities. The company currently has a network of over 40,000 artisans spread across 600 rural Indian villages in five states of India. It has an end-to-end business model, right from sourcing of wool to exporting a finished handmade rug.

The modern and eclectic collection of rugs, made using the finest wool and silk, has won numerous global awards and is currently exported to more than 45 countries with the US sales arm, Jaipur Living, Inc. located in Georgia, Atlanta.

Job Description : The specific responsibilities of the position holder will be (though not restricted to) the following :

  • The Data Engineer will be responsible for building and maintaining end-to-end data pipelines for analytics solutions , leveraging Microsoft Fabric to integrate Business applications to Jaipur Living BI platform
  • Build and maintain end-to-end data pipelines across business application and BI platform
  • Develop and implement solutions on the MS Fabric platform to support a modern enterprise data platform by implementing Kimball Data Lakehouse (Fact and Dim)
  • Design, develop, and implement analytics solutions on MS Fabric and PowerBI
  • Develop ETL / ELT processes for large-scale data ingestion, ensuring data quality and pipeline performance
  • Transform and model data to meet business requirements, loading it into Fabric Data Lakehouse (bronze, silver, gold layers)
  • Implement monitoring and error handling processes for reliable data integration
  • Optimize pipelines for cost and performance through query tuning, caching, and resource management
  • Automate repeatable data preparation tasks to reduce manual processes
  • Provide troubleshooting, analysis, and production support for existing solutions , including enhancements
  • Integrate GitHub for artifact management and versioning
  • Continuous Improvement – Identifies opportunities, generates ideas, and implements solutions to improve processes and conditions

Skills

  • Minimum of 5 years of hands-on experience building data pipelines, data models, and supporting enterprise data warehouse solutions
  • Hands-on experience with Microsoft Fabric for data pipelines , Gen2 Data Flows , Activity optimization , Data Modeling , and analytics
  • Proficiency with Microsoft Fabric data services, including Azure Synapse Analytics and Dataverse
  • Strong SQL, data modeling, and ETL / ELT development skills
  • Experience working within a scaled agile framework for data engineering product delivery
  • 4+ years of experience with ETL and cloud data technologies, including Azure Data Lake , Azure Data Factory , Azure Synapse , Azure Functions , Azure Data Explorer , and Power BI (or equivalent platforms) and Google Big Query
  • 4+ years of experience in big data scripting languages such as Python, or SQL
  • 4+ years of experience in one scripting language for data retrieval and manipulation (e.g., SQL)
  • Strong SQL, data modeling, data warehouse, and OLAP concepts
  • Experience with Azure Data Lake Storage, Azure Synapse Analytics, Fabric Spark Pools, Fabric Notebooks, Python, DevOps, and CI / CD
  • Familiarity with data lake medallion architecture and unified data models for BI platform
  • Familiarity with Scaled Agile, DevOps, Scrum, and ITIL concepts
  • Retail experience will be a plus
  • WMS, ERP, CRM, PIM, Google Analytics experience is a plus
  • Microsoft Dynamics ERP experience is a plus
  • Experience with Fabric AI services will be a plus
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    Data Engineer • Nagpur, IN

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