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 environments.
- 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.
- Strong 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 (Bengaluru)
🏢 Tiger Analytics
📍 Bengaluru