Hadoop Data Engineer

Role: Lead Data Engineer

Location: Hyderabad

Experience: 6 to 10 years

*Preferred: Immediate joiners*

Key Responsibilities

• Design, build, and maintain scalable ETL/ELT data pipelines using Hadoop, Hive, HDFS, and Spark/PySpark
• Develop and optimize complex SQL queries and Hive scripts for large-scale data processing
• Write clean, efficient, and reusable Python code for data transformation and automation
• Work with structured and unstructured data across distributed storage systems (HDFS)
• Optimize Spark/PySpark jobs for performance, scalability, and resource efficiency
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements
• Ensure data quality, consistency, and integrity across pipelines
• Troubleshoot and resolve issues related to data pipeline failures, performance bottlenecks, and cluster resource management
• Participate in code reviews and follow best practices for data engineering and version control
• Document technical designs, data flows, and pipeline architecture

Required Skills & Experience

• 6 10 years of hands-on experience in Data Engineering
• Strong working knowledge of Hadoop ecosystem (HDFS, YARN, MapReduce concepts)
• Proficiency in Hive for data warehousing and query optimization
• Solid experience with Spark/PySpark for distributed data processing
• Strong programming skills in Python
• Advanced SQL skills query optimization, joins, window functions, performance tuning