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Data Engineer - Data Platforms - Azure

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Onsite

Data Engineer - Data Platforms - Azure

IBM

Data Engineer - Data Platforms - Azure

Skills

SQL QueriesData EngineeringPythonMicrosoft Azure Cosmos DBDatabricksData AnalysisScaladbtApache AirflowAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

11 August 2026

What they need


Your Role and Responsibilities:

As a Data Engineer specializing in Data Platforms on Azure, you will advise on, develop, and maintain data engineering solutions on the Azure Cloud ecosystem. You will design, build, and operate batch and real-time data pipelines using various Azure services.

Your primary responsibilities will include:

  • Design and Build Data Pipelines: Design, build, and operate batch and real-time data pipelines using Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub.
  • Develop Data Layer: Design, build, and operate the data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB.
  • Implement Azure Data Platform: Implement and maintain Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB.
  • Utilize Open Source Technologies: Apply proficiency in open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to support data engineering solutions.
  • Ensure Seamless Operations: Operate and maintain data engineering solutions to ensure seamless batch and real-time data processing.

Required Education:

Bachelor's Degree

Preferred education

Master's Degree

Required Technical and Professional Expertise:

  • Exposure to Azure Toolset: Proficiency in Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub to design, build, and operate batch and real-time data pipelines.
  • Data Engineering on Azure: Experience working with Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB.
  • Open Source Technologies: Exposure to open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to support data engineering solutions.
  • Data Pipeline Development: Experience developing and maintaining data engineering solutions on the Azure Cloud ecosystem, including designing, building, and operating batch and real-time data pipelines.
  • Azure Data Layer Design: Experience designing, building, and operating the data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB.

Preferred Technical and Professional Experience:

  • Proficiency in Azure Services: Exposure to Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub to design, build, and operate batch and real-time data pipelines.
  • Open Source Technologies: Exposure to open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to support data engineering solutions.
  • Data Engineering on Azure: Experience working with Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB.

Years of Experience:
5 - 8

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