Role & responsibilities
Develop and support Azure Data Engineering pipelines using Azure Databricks, Azure Data Factory, and ADLS Gen2.
Troubleshoot production issues in PySpark, Spark SQL, and ETL/ELT workflows.
Write and optimize complex SQL queries for data processing and validation.
Monitor pipeline performance and resolve job failures.
Perform root cause analysis (RCA) and implement preventive measures.
Support data migration, ingestion, and transformation across settings.
Provide L3 production support and maintain technical documentation.

Preferred candidate profile
2+ years of experience in Data Engineering Support or L2/L3 Production Support.
Hands-on experience with Azure Databricks, Python, SQL, and Azure Cloud.
Robust SQL skills,



including complex queries, joins, CTEs, and query optimization.
Valuable understanding of ETL/ELT pipelines, data ingestion, and data transformation.
Familiarity with PySpark, Spark SQL, Azure Data Factory, and ADLS Gen2 is preferred.
Experience with incident management, troubleshooting, and root cause analysis.
Familiarity with ServiceNow, monitoring tools, and production support processes.

Experience in L3 production support is mandatory

Looking for immediate joiners or candidates who can join by October 2026.

📌 Support + Azure Databricks Junior System Engineer/system Engineer Chennai
🏢 Tiger Analytics
📍 Chennai