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    Job · 19520963

    HYDERABAD · FULLTIME

    Data Engineer-Data Platforms-Azure

    IBM logo

    IBM

    Hyderabad · onsite · Posted 23d ago

    Sourced fromNaukri
    Undisclosed12–14 yrsfulltimeHyderabad

    About a minute. You'll make an account on the way through.

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    Section · 01

    About this role

    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, ensuring seamless data integration and management.
    Leverage Azure Data Platform: Utilize Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB, to develop and maintain scalable data solutions.
    Implement Open Source Technologies: Apply expertise in open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to enhance data engineering solutions.
    Ensure Data Quality: Collaborate to ensure high-quality data delivery, adhering to data governance and compliance standards.
    Required Education:
    Bachelor's Degree
    Preferred education
    Master's Degree
    Required Technical and Professional Expertise:
    Azure Data Engineering Expertise: Experience with designing, building, and operating batch and real-time data pipelines using Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub.
    Data Layer Development: Experience in designing, building, and operating the data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB, ensuring seamless data integration and management.
    Azure Data Platform Proficiency: Experience 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: Experience with open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala in data engineering solutions.
    Data Quality Assurance: Experience in ensuring high-quality data delivery, adhering to data governance and compliance standards in a cloud-based data engineering environment.
    Preferred Technical and Professional Experience:
    Proficiency in Apache Kafka: Experience with Managed Streaming for Apache Kafka is beneficial for enhancing real-time data pipeline capabilities.
    Knowledge of Azure Functions: Familiarity with Azure functions with Python is advantageous for developing scalable data solutions.
    Exposure to dbt: Experience with dbt is valuable for applying data transformation techniques in data engineering solutions.
    Years of Experience:
    12 - 14

    Sourced from naukri

    Section · 02

    Skills

    Apache SparkdataSQL AzureAnalyticsPythonPower BiTableauSQLData WarehousingAzure Data FactoryAzure DatabricksAzure Data Lakedata analysisData Entry OperationETLexcelMicrosoft AzureSQL ServerBig DataMachine Learning

    Section · Company

    About IBM

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    IBM

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