Hadoop Data Engineer

Location: Hyderabad

Experience: 3–6 Years

Employment Type: Full time

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

- 3–6 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

Good to Have

- Experience with NoSQL databases (HBase, Cassandra) - Familiarity with CI/CD pipelines for data engineering workflows

Educational Qualification

- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field

Regards,

Manvendra Singh [email protected]

📌 Hadoop Data Engineer (Hyderabad)
🏢 Incedo
📍 Hyderabad