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Open nowFirst seen 3 days ago

Azure Data Engineer with Snowflake Experience

PradeepIT Consulting Services Pvt Ltd2,005 open roles

Where
Bengaluru, KA, India, Remote
Work mode
Remote
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Your applicationOpen nowAzure Data Engineer with Snowflake ExperiencePradeepIT Consulting Services Pvt Ltd · Bengaluru, KA, India, Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on PradeepIT Consulting Services Pvt Ltd's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

The posting

Job Description:

We are seeking an experienced and skilled Azure Data Engineer with significant expertise in Snowflake to join our dynamic team. The ideal candidate should possess in-depth knowledge of Azure data services, and Snowflake, and have a proven track record in designing, developing, and maintaining robust data solutions.

Key Responsibilities:

1. Data Solution Design:- Collaborate with stakeholders to understand data requirements and design scalable and efficient data solutions using Azure services and Snowflake.

2. Data Modeling: - Develop and implement data models that align with business requirements and ensure optimal performance in Snowflake.

3. ETL Development: Design, develop, and maintain ETL processes to extract, transform, and load data from various sources into Snowflake using Azure Data Factory or other relevant tools.

4. Data Integration: Implement seamless data integration solutions between Azure and Snowflake platforms.

5. Optimization and Performance Tuning: Identify and resolve performance bottlenecks, optimize queries, and ensure the overall efficiency of data pipelines.

6. Data Security and Compliance: Implement and maintain data security measures, ensuring compliance with industry standards and regulations.

7. Monitoring and Maintenance: Set up monitoring processes to proactively identify issues, and perform routine maintenance tasks to ensure data integrity and system stability.

8. Documentation: Create and maintain comprehensive documentation for data engineering processes, configurations, and best practices.

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