Azure Data Factory (ADF)

Infosys; Pune District, Chennai District, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Infosys is seeking an experienced Azure Data Factory specialist in Pune to design, develop and maintain scalable data pipelines using Azure services. The role requires 5-8 years of experience in data engineering and deep knowledge of ETL/ELT processes.

You will work with Azure Databricks, ADLS and Azure SQL to ingest, transform and deliver data assets. Collaboration with analytics teams and adherence to CI/CD deployment practices are essential.

Qualifications

• 5-8 years of experience in data engineering or related field.
• Experience designing and implementing data pipelines on Azure.
• Strong understanding of ETL/ELT processes and data quality.

Responsibilities

• Design, develop, and maintain data pipelines using Azure Data Factory.
• Build ETL/ELT solutions for data ingestion and transformation.
• Integrate data from multiple on-premises and cloud sources.
• Work with Azure Databricks, ADLS, and Azure SQL.
• Monitor and optimize pipeline performance and reliability.
• Implement data quality and validation checks.
• Automate deployments using CI/CD and DevOps practices.
• Collaborate with business and analytics teams on data requirements.

Skills

Data pipeline design

ETL/ELT development

Cloud data integration

Collaboration with analytics teams

Tools

Azure Data Factory

Azure Databricks

ADLS

Azure SQL

Job description

Job Description:

Position: Azure Data Factory

Experience: 5-8YRS

Roles & Responsibilities

• Design, develop, and maintain data pipelines using Azure Data Factory.
• Build ETL/ELT solutions for data ingestion and transformation.
• Integrate data from multiple on-premises and cloud sources.
• Work with Azure Databricks, ADLS, and Azure SQL.
• Monitor and optimize pipeline performance and reliability.
• Implement data quality and validation checks.
• Automate deployments using Azure DevOps and CI/CD.
• Collaborate with business and analytics teams on data requirements.