Data Lead with Azure Data Factory (ADF), DataBricks

TechDigital

  • Dallas, TX
  • 3 days ago

    Highlights

    Stay updated on industry trends and best practices related to snowflake, azure data factory (adf), and data bricks to recommend and implement improvements in existing data processes. 4. Troubleshoot and resolve technical issues related to data pipelines, data transformation, and data storage in snowflake, azure data factory (adf), and data bricks.

    Numbers & Facts

    LocationDallas, TX
    IndustryOther/Not Classified
    Company Size100 to 499 employees

    Description

    Data Lead with Azure Data Factory (ADF), DataBricks

    Job Summary
    The Technical Lead will be responsible for leading and managing the implementation, maintenance, and support of Snowflake, Azure Data Factory (ADF), and Data Bricks solutions. The role involves overseeing the technical aspects of projects related to data engineering, data integration, and data processing using these platforms. (1.) Key Responsibilities
    1. Lead the design, development, and deployment of snowflake, azure data factory (adf), and data bricks solutions according to project requirements.
    2. Collaborate with cross functional teams to gather data requirements, design data pipelines, and ensure data quality and integrity.
    3. Provide technical guidance and mentorship to team members on best practices for utilizing snowflake, azure data factory (adf), and data bricks.
    4. Troubleshoot and resolve technical issues related to data pipelines, data transformation, and data storage in snowflake, azure data factory (adf), and data bricks.
    5. Stay updated on industry trends and best practices related to snowflake, azure data factory (adf), and data bricks to recommend and implement improvements in existing data processes.

    Skill Requirements
    1. Proficiency in snowflake architecture, implementation, and optimization.
    2. Handson experience with azure data factory (adf) including data pipeline development, integration, and monitoring.
    3. Strong knowledge of data bricks for big data processing, data engineering, and machine learning workflows.
    4. In-depth understanding of data warehousing concepts, etl processes, and data modeling techniques.
    5. Excellent problem-solving skills and ability to work in a fast paced environment.
    6. Strong communication and leadership skills to effectively collaborate with team members and stakeholders.

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