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
- Solid 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