Big Data Engineer (Hadoop)

5 - 8 years

4 - 7 Lacs

Posted:1 week ago| Platform: Foundit logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Key Responsibilities:

  • Design, develop, and optimize large-scale data processing workflows using Hadoop components such as

    HDFS, MapReduce, Hive, Pig, and HBase

    .
  • Build and maintain ETL pipelines to ingest and transform data from various sources into Hadoop clusters.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality data solutions.
  • Ensure data quality, integrity, and security within big data environments.
  • Monitor and troubleshoot Hadoop cluster performance and resolve issues proactively.
  • Implement best practices for data storage, processing, and retrieval in Hadoop ecosystems.
  • Develop automation scripts for data pipeline orchestration and workflow management (using tools like Apache Oozie or Airflow).
  • Participate in capacity planning, cluster management, and Hadoop upgrades.
  • Document data architecture, workflows, and operational procedures.

Qualifications and Requirements:

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or related field.
  • 3+ years of experience as a Big Data Engineer or Hadoop Developer.
  • Hands-on experience with core Hadoop ecosystem components:

    HDFS, MapReduce, Hive, Pig, HBase, Sqoop, Flume

    .
  • Strong proficiency in

    Java, Scala, or Python

    for big data processing.
  • Experience with data modeling and query optimization in Hive or HBase.
  • Familiarity with data ingestion techniques and tools (Sqoop, Flume, Kafka).
  • Understanding of cluster management and resource schedulers like YARN.
  • Knowledge of Linux/Unix environments and shell scripting.
  • Experience with version control (Git) and CI/CD pipelines.
  • Strong analytical and problem-solving skills.

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