How much salary can I expect as a Azure Databricks Administrator in Infosys in Bengaluru/Bangalore?

You can expect a minimum salary of 0 INR. The salary offered will depend on your skills, experience and performance in the interview.

What is the eligibility criteria to apply for Azure Databricks Administrator in Infosys in Bengaluru/Bangalore?

The candidate should have completed the required education and people who have 2 to 14 years are eligible to apply for this job. You can apply for more jobs in Bengaluru/Bangalore to get hired quickly.

Is there any specific skill required for this job?

The candidate should have sound communication skills and sound communication skills for this job.

Who can apply for this job?

Both Male and Female candidates can apply for this job.

Is it a work from home job?

No, it's not a work from home job and can't be done online. You can explore and apply for other work from home jobs in Bengaluru/Bangalore at apna.

Are there any charges or deposits required while applying for the role or while joining?

No work-related deposit needs to be made during your employment with the company.

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Go to the apna app and apply for this job. Click on the apply button and call HR directly to schedule your interview.

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Azure Databricks Administrator

Infosys

Azure Databricks Administrator

Infosys

Bengaluru/Bangalore

Not disclosed

Work from Office

Full Time

Min. 2 years

Job Description

Azure databricks admin

Strong hands-on experience with Azure Databricks Proficient in Apache Spark (PySpark/Scala) Experience with Azure Data Lake (ADLS Gen2) and cloud storage Strong SQL skills and experience with large datasets Experience with Azure Data Factory (ADF) for orchestration Knowledge of data modeling, partitioning, and performance tuning Experience working with big data frameworks Design, develop, and maintain data pipelines using Azure Databricks Implement ETL/ELT workflows to process large-scale structured and unstructured data Optimize Spark jobs for performance, scalability, and cost Work with Azure Data Lake Storage (ADLS Gen2), Azure Blob Storage, and Azure SQL Develop and manage Databricks notebooks using PySpark / Scala / SQL Integrate Databricks with Azure services such as: Azure Data Factory Azure Synapse Analytics Azure Key Vault Implement data quality, validation, and monitoring frameworks