HADOOP DATA ENGINEER ROLE

Location: Bangalore
Experience: 8–12 Years
Work Mode: Hybrid
Joining: Mid to Last Week of September

Job Description

We are looking for an experienced Hadoop Data Engineer with strong hands-on expertise in Python, PySpark, Hadoop, and SQL . The ideal candidate should have experience in developing and optimizing large-scale data pipelines and working with distributed data processing technologies.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python and PySpark.
• Work with Hadoop ecosystem for large-scale data storage and processing.
• Develop complex and optimized SQL queries for data extraction and transformation.
• Perform data cleansing, transformation, and integration from multiple sources.
• Optimize PySpark and Hadoop jobs for better performance and scalability.
• Troubleshoot data pipeline and production issues.
• Collaborate with data engineers, analysts, and business teams to deliver reliable data solutions.
• Ensure data quality, accuracy, and consistency across pipelines.

Must-Have Skills

• 8–12 years of experience in Data Engineering.
• Strong hands-on experience with Python .
• Strong expertise in PySpark .
• Hands-on experience with Hadoop / HDFS .
• Strong SQL skills.
• Experience in developing and optimizing ETL/ELT data pipelines .
• Good understanding of distributed data processing and large-scale datasets.

Good to Have

• Experience with Hive, YARN, MapReduce, Spark .
• Experience with cloud platforms such as AWS / Azure / GCP .
• Experience with data warehousing and Big Data technologies.
• Knowledge of data quality and performance optimization.