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