Lead Data Engineer

12 - 15 years

30 - 45 Lacs

Posted:1 day ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

  • Experience - 12 - 15 years

  • Responsible for the design, implementation, and optimization of data solutions as an expert

    Azure Data Engineer with 6-8 years of experience.

  • Proficiency in programming languages like

    Python, SQL, or Scala for data manipulation, transformation, and analysis

  • Expertise in data modelling, data warehousing, and data integration concepts.
  • Sound knowledge of data governance practices, data quality management, and data security principles.
  • Develop efficient ETL pipelines using Azure Data Factory and ensure data quality and storage via

    Azure Data Lake.

  • Utilize your proficiency in complex stored procedures within Azure Databricks to enable advanced analytics on

    data volumes exceeding 50TB.

  • Collaborate cross-functionally to contribute to data-driven initiatives, leveraging Azure Synapse Analytics to provide actionable insights.
  • Apply your deep understanding of the retail domain to enhance data strategies and solutions for retail-specific challenges.
  • Play a pivotal role in shaping our organization's data-driven journey, driving innovation through data analytics and insights.
  • Optimize

    data storage, processing and retrieval mechanisms

    for performance, cost, and scalability using data storage services (such as Azure Data Lake Storage, Azure SQL Database, etc.), data processing services (such as Azure Data Bricks, Azure Synapse, etc.) and data visualization (

    PowerBI, Qlik

    , etc.) & integration services (

    Data API builder, logic apps, etc

    .)
  • Monitor and troubleshoot data platform performance, identify and resolve issues, and provide recommendations for continuous improvement.
  • Collaborate with DevOps teams to automate deployment, configuration, and monitoring processes using

    Azure DevOps

    , PowerShell, or other relevant tools.
  • Stay up to date with the latest trends and advancements in cloud data services and provide recommendations on adopting new technologies or features to enhance the data platform.
  • Document technical designs, procedures, and guidelines for data platform engineering and operations

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