Looking for Azure Data Engineer at Cincinnati, OH/Onsite only locals

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vin...@virtualnetworx.in

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Jan 20, 2026, 5:18:31 PMJan 20
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Hello Partner's

This is Vinay from virtual Networx inc. please go through below priority requirements and share me suitable resumes to 


Vin...@virtualnetworx.com 


Title: Azure Data Engineer

Location: Cincinnati, OH/Onsite

Need Only locals

 

Job Description:

Overview

We are seeking a Data Engineer to join our team in Cincinnati, Ohio. The ideal candidate will have strong expertise in Azure, Databricks, Python, and Power BI, with a proven ability to design, build, and optimize data pipelines and reporting solutions.

 

Key Responsibilities

  • Design and develop data pipelines using Azure Data Factory, Databricks, and other cloud-native tools.
  • Implement ETL processes to ensure efficient data ingestion, transformation, and storage.
  • Collaborate with business stakeholders to understand reporting needs and deliver actionable insights.
  • Develop and maintain dashboards in Power BI to support decision-making across teams.
  • Optimize data workflows for performance, scalability, and reliability.
  • Ensure data quality and governance standards are met across all systems.
  • Troubleshoot and resolve issues related to data pipelines, integrations, and reporting.

 

Required Skills & Qualifications

  • Hands-on experience with Microsoft Azure (Data Factory, Synapse, Storage, etc.).
  • Proficiency in Databricks for big data processing and analytics.
  • Strong Python programming skills for data manipulation, automation, and integration.
  • Expertise in Power BI for dashboard creation and data visualization.
  • Solid understanding of SQL and relational database concepts.
  • Experience with data modeling and performance tuning.
  • Excellent communication skills to work effectively with technical and non-technical stakeholders.

 

Preferred Qualifications

  • Experience with CI/CD pipelines for data solutions.
  • Knowledge of cloud security best practices.
  • Background in data warehousing and analytics.
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