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Job Type

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Job Description

Big Data Engineer (PySpark)

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Job Overview

Big Data Engineer


Key Responsibilities

  • Design, develop, and maintain data pipelines using

    PySpark

    and related Big Data technologies.
  • Work with

    HDFS, Hive, Sqoop

    , and other tools in the Hadoop ecosystem.
  • Write efficient

    HiveQL and SQL

    queries to handle large-scale datasets.
  • Perform

    performance tuning and optimization

    of distributed data systems.
  • Collaborate with cross-functional teams in an

    Agile environment

    to deliver high-quality solutions.
  • Manage and schedule workflows using

    Apache Airflow

    or

    Oozie

    .
  • Troubleshoot and resolve issues in data pipelines to ensure reliability and accuracy.


Required Skills

  • Proven experience in

    Big Data Engineering

    with a focus on PySpark.
  • Strong knowledge of

    HDFS, Hive, Sqoop

    , and related tools.
  • Proficiency in

    SQL/HiveQL

    for large datasets.
  • Expertise in

    performance tuning and optimization

    of distributed systems.
  • Familiarity with

    Agile methodology

    and collaborative team practices.
  • Experience with workflow orchestration tools (

    Airflow/Oozie

    ).
  • Strong

    problem-solving, analytical, and communication

    skills.


Good to Have

  • Knowledge of

    data modeling

    and

    data warehousing

    concepts.
  • Exposure to

    DevOps practices

    and

    CI/CD pipelines

    for data engineering.
  • Experience with other Big Data frameworks such as

    Spark Streaming

    or

    Kafka

    .

Mock Interview

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