Hadoop Developer

Codinix Technologies Inc.; United States; Hybrid; USD 120,000 - 130,000; Full time

Job summary

Codinix Technologies Inc. is seeking an experienced Hadoop Developer to design, develop, and maintain scalable big data solutions using the Hadoop ecosystem.

The role focuses on distributed data processing, data pipeline development, and supporting enterprise analytics initiatives. You will collaborate with data analysts, engineers, and data scientists to optimize performance, ensure data integrity, and adhere to governance and security standards while delivering with Hive, Pig, Spark, and

Qualifications

• 8+ years of experience in Hadoop and Big Data development.
• Strong hands-on experience with Hadoop ecosystem including HDFS, MapReduce, Hive, and Pig.
• Proficiency in SQL and scripting languages such as Python and Shell scripting.

Responsibilities

• Develop, maintain, and enhance big data applications using Hadoop ecosystem technologies.
• Design and implement scalable data pipelines using Hive, Pig, Spark, and related tools.
• Write efficient MapReduce and Apache Spark jobs for large-scale data processing.
• Ingest, transform, and load structured and unstructured data from multiple data sources.
• Collaborate with data analysts, engineers, and data scientists to support analytics and reporting needs.
• Optimize data workflows, improve processing performance, and ensure data integrity.
• Troubleshoot and resolve issues related to big data processing and system performance.

Skills

Hadoop ecosystem

Spark

SQL

Python

Shell scripting

ETL

Linux/Unix

Analytical thinking

Team collaboration

Tools

HDFS

MapReduce

Hive

Pig

Apache Spark

Job description

Salary Range: $120,000 – $130,000
Job Type: Full-Time

Job Overview

We are seeking an experienced Hadoop Developer to design, develop, and maintain scalable big data solutions using the Hadoop ecosystem. The ideal candidate will have strong expertise in distributed data processing, data pipeline development, and big data technologies. This role requires working with large datasets, optimizing performance, and supporting enterprise analytics initiatives.

Key Responsibilities

• Develop, maintain, and enhance big data applications using Hadoop ecosystem technologies
• Design and implement scalable data pipelines using Hive, Pig, Spark, and related tools
• Write efficient MapReduce and Apache Spark jobs for large-scale data processing
• Ingest, transform, and load structured and unstructured data from multiple data sources
• Manage and maintain data storage within HDFS environments
• Collaborate with data analysts, engineers, and data scientists to support analytics and reporting needs
• Optimize data workflows, improve processing performance, and ensure data integrity
• Troubleshoot and resolve issues related to big data processing and system performance
• Ensure adherence to data governance, security, and quality standards

Required Skills

• Strong hands-on experience with the Hadoop ecosystem including HDFS, MapReduce, Hive, and Pig
• Experience with Apache Spark for distributed data processing
• Proficiency in SQL and scripting languages such as Python and Shell scripting
• Solid understanding of ETL processes and data warehousing concepts
• Experience working in Linux/Unix environments
• Strong analytical and problem-solving abilities
• Ability to work effectively in a collaborative team environment

Preferred Skills

• Experience with Kafka, Sqoop, or Flume
• Knowledge of cloud-based big data platforms is a plus
• Familiarity with workflow orchestration tools and automation frameworks

Experience Required

• 8+ years of experience in Hadoop and Big Data development