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Snowflake + Azure Data Engineer

5 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Contractual

Job Description

full time remote contract


overlapping time with US timezone


You may need to go through the background verification process in which your claimed experience, education certificates and references given will be verified. So pls don't apply if you are not comfortable to go through this verification process.


communication in English language is MUST


Min. Experience : 5+ years


About role :

Our client is about to start an ERP replacement. They plan to move away from the AWS platform and move to an Azure data lake feeding Snowflake. We need a resource who can be Snowflake thought leader and having Microsoft azure data engineering expertise.


Key Responsibilities:


Data Ingestion & Orchestration (Transformation & Cleansing) :

Design and maintain Azure Data Factory (ADF) pipelines

Extract data from sources like ERPs (SAP, Oracle), UKG, SharePoint, and REST APIs.

Configure scheduled/event-driven loads

Transform and cleanse data

Implement data quality checks

Snowflake Data Warehousing:

Design/optimize data models:

ETL/ELT in Snowflake:

Performance tuning:

Implement ETL/ELT


Data Lake Management:

Implement Azure Data Lake Gen2 solutions

Manage partitioning, security, governance:


Collaboration & Documentation:

Monitoring & Support:

Data visualization tools

Skilled in Python


Required Skills & Qualifications:

  • Over 5+ years of experience

    in data engineering, data warehousing, or ETL development.
  • Microsoft Azure proficiency:

  • Azure Data Factory (ADF):

    Experience in designing, developing, and deploying complex data pipelines.
  • Azure Data Lake Storage Gen2:

    Hands-on experience with data ingestion, storage, and organization.
  • Expertise in Snowflake Data Warehouse and ETL/ELT:

  • Understanding Snowflake architecture.
  • SQL proficiency for manipulation and querying.
  • Experience with Snowpipe, tasks, streams, and stored procedures.
  • Strong understanding of data warehousing concepts and ETL/ELT principles.
  • Data Formats & Integration :

    Experience with various data formats (e.g., Parquet, CSV, JSON) and data integration patterns.
  • Data Visualization:

    Experience with Power BI, DAX, Power Query.
  • Scripting:

    Python for data processing and analysis.
  • Soft Skills:

     Problem-solving, attention to detail, communication, and collaboration

Nice-to-Have Skills


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