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    Job · 12018966

    REMOTEFULLTIME

    Data Engineer II

    Inxite Out logo

    Inxite Out

    Remote · remote · Posted 65d ago

    Sourced fromNaukri
    Undisclosed3–4 yrsfulltimeRemote

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

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    Section · 01

    About this role

    Job Summary


    We are looking for a Data Engineer with 3+ years of experience in Python/PySpark, SQL, Data Warehousing, and Azure ETL to build scalable and reliable data pipelines.


    Key Responsibilities

    • Develop and maintain data pipelines using Python/PySpark.
    • Build ETL/ELT solutions using Azure Data Factory, Data Lake, Blob Storage, Databricks, Synapse, and Azure SQL.
    • Write complex SQL queries, stored procedures, and transformations.
    • Collaborate with business and technical teams to deliver data solutions.
    • Troubleshoot data and pipeline issues and follow engineering best practices.
    • Use Git, Azure DevOps, and Jira for development and project tracking.

    Required Skills

    • 3+ years of experience in Data Engineering/Data Warehousing.
    • Strong Python/PySpark and SQL skills.
    • Hands-on experience with Azure data services and ETL.
    • Good understanding of data integration and data warehousing.
    • Strong analytical, problem-solving, and communication skills.

    Preferred

    • Azure Databricks/Spark experience.
    • Azure Data Engineer certification is a plus.

    Role: Data Engineer | Employment: Full-Time, PermanentEducation: B.Sc./BCA/B.Tech/B.E. or any Postgraduate degree


    Sourced from naukri

    Section · 02

    Skills

    Blob StoragePysparkData EngineeringPythonSQLData WarehousingAzure Data FactoryAzure DatabricksAzure Data LakeETLMicrosoft Azure

    Section · Company

    About Inxite Out

    Inxite Out logo

    Inxite Out

    Analytics & KPO

    51-200

    employees

    2019

    7 years old

    Kolkata, West Bengal

    India

    ₹13.8L PA avg

    Avg at Inxite Out

    About

    Inxite Out helps businesses leverage data and AI to achieve transformative outcomes, focusing on aligning data with technology and business objectives.

    Industries

    Analytics & KPO

    Employee ratings

    10 reviews

    4.3/ 5

    Culture

    3.5

    Career growth

    3.5

    Work-life

    3.6

    Employees rate it well for

    Job Security44Overall Company43

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