Role & responsibilities

- Develop and maintain scalable Big Data solutions using the Hadoop ecosystem.
- Work with HDFS, Hive, Spark, Sqoop, Oozie, and YARN.
- Develop and optimize Hive SQL queries and data transformations.
- Build batch-processing and ETL pipelines using Apache Spark.
- Perform data ingestion from relational databases and external sources using Sqoop or equivalent tools.
- Manage data storage, partitioning, bucketing, compression, and schema evolution.
- Monitor and troubleshoot Hadoop jobs and cluster performance.
- Work with Python / Scala / Java for data processing.
- Implement data quality, validation, and reconciliation processes.
- Collaborate with Data Architects, Analysts, and application teams to deliver data solutions.
- Optimize Spark/Hadoop jobs for performance and resource utilization.

Preferred candidate profile

- Hadoop
- HDFS
- Hive / HiveQL
- Apache Spark
- YARN
- SQL
- Big Data ETL
- Data Warehousing
- Python / Scala / Java
- Distributed computing concepts
- Performance tuning and troubleshooting

📌 Technical Lead (Bengaluru)
🏢 software
📍 Bengaluru