: Cloud Data Engineer

Experience: 5 8 Years

Relevant Experience: Minimum 5+ Years

Location: Bangalore

Work Mode: Hybrid 3 Days a Week in Office

Job Summary

We are looking for an experienced Cloud Data Engineer with strong hands-on expertise in Hadoop, HDFS, Hive, and PySpark. The ideal candidate should have solid experience in big data processing, distributed computing, data transformation, and building scalable data pipelines.

Key Responsibilities

- Design, develop, and maintain scalable data processing pipelines using PySpark.
- Work with Hadoop and HDFS for distributed data storage and processing.
- Develop, optimize, and maintain Hive queries, tables, and data models.
- Perform large-scale data extraction, transformation, and loading (ETL) using PySpark and Hadoop ecosystem technologies.
- Optimize Spark jobs and Hive queries for performance and resource utilization.
- Handle structured and semi-structured data for analytics and reporting requirements.
- Troubleshoot data pipeline failures, data quality issues, and performance bottlenecks.




- Collaborate with data engineers, analysts, and other stakeholders to deliver reliable data solutions.
- Follow best practices for data security, data quality, code maintenance, and performance optimization.

Required Skills

- Hadoop: Strong hands-on experience with the Hadoop ecosystem.
- HDFS: Experience managing and processing data in the Hadoop Distributed File System.
- Hive: Proficiency in HiveQL, query optimization, and data management.
- PySpark: Strong hands-on experience in distributed data processing and transformation.
- Big Data: Positive understanding of distributed computing and large-scale data processing.
- ETL/Data Pipelines: Experience developing, maintaining, and optimizing data pipelines.
- SQL: Strong query-writing and data manipulation skills.
- Troubleshooting: Ability to identify and resolve data processing and performance issues.

📌 Cloud Data Engineer (Karnataka)
🏢 SWITS DIGITAL Private
📍 Karnataka