Urgent Opening Azure Data Engineer-(Chennai/Mumbai)

SP Staffing; Chennai District, Mumbai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

SP Staffing Services Pvt. Ltd. is seeking a highly experienced Azure Data Engineer in Chennai/Mumbai to design, develop and maintain scalable data pipelines.

Applicants should have 5+ years of experience with ADF, Databricks and Synapse, SQL, Python and PySpark, plus CI/CD using Azure DevOps. The role focuses on data lake/warehouse implementations and cost-effective pipeline operations.

Qualifications

• Design, develop and maintain scalable Azure data pipelines.
• Build ETL/ELT solutions using ADF, Databricks and Synapse.
• Develop data lake and data warehouse solutions using ADLS Gen2 and Synapse.
• Write optimized SQL, Python and PySpark code.
• Develop Spark/Databricks transformations for large datasets.
• Implement incremental/CDC data-loading patterns.
• Monitor, troubleshoot and optimize pipelines for performance and cost.
• Implement data quality, security and governance.
• Use Azure DevOps/Git for CI/CD and source-code management.
• Work with architects, analysts and business teams to deliver data solutions

Responsibilities

• Design, develop and maintain scalable Azure data pipelines.
• Build ETL/ELT solutions using ADF, Databricks and Synapse.
• Develop data lake and data warehouse solutions using ADLS Gen2 and Synapse.
• Write optimized SQL, Python and PySpark code.

Skills

Data pipeline design

ETL/ELT concepts

SQL proficiency

Python programming

PySpark

Data quality & governance

Cost optimization

CI/CD concepts

Collaboration with teams

Tools

ADF

Databricks

Synapse

ADLS Gen2

Azure DevOps

Git

SQL

Python

PySpark

Job description

Warm Greetings from SP Staffing Services Pvt. Ltd.!

We are looking for highly experienced Azure Data Engineer

Experience: 5+
Work Location: Chennai/Mumbai

Key Requirements:

1. Design, develop and maintain scalable Azure data pipelines.
2. Build ETL/ELT solutions using ADF, Databricks and Synapse.
3. Develop data lake and data warehouse solutions using ADLS Gen2 and Synapse.
4. Write optimized SQL, Python and PySpark code.
5. Develop Spark/Databricks transformations for large datasets.
6. Implement incremental/CDC data-loading patterns.
7. Monitor, troubleshoot and optimize pipelines for performance and cost.
8. Implement data quality, security and governance.
9. Use Azure DevOps/Git for CI/CD and source-code management.
10. Work with architects, analysts and business teams to deliver data solutions