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U
Unison GroupKuala Lumpur, Malaysia

Big Data Hadoop Developer

Posted over a year agoData Engineer

At a glance

Posted
14 August 2025
Type
Full-time
Country
Malaysia
Skills named
aws, azure, bash, cassandra, data migration, etl, gcp, git
Application form
Workable

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  • Job Summary:
  • We are looking for a Big Data Hadoop Developer to design, develop, and maintain large-scale data processing solutions. The ideal candidate should have strong hands-on experience with the Hadoop ecosystem and integration with relational databases such as MariaDB or Oracle DB for analytics and reporting.
  • Key Responsibilities:
  • Design, develop, and optimize Hadoop-based big data solutions for batch and real-time data processing.
  • Work with data ingestion frameworks to integrate data from MariaDB/Oracle DB into Hadoop (Sqoop, Apache Nifi, Kafka).
  • Implement Hive, Spark, and MapReduce jobs for data transformation and analytics.
  • Optimize Hive queries, Spark jobs, and HDFS usage for performance and cost efficiency.
  • Create and maintain ETL pipelines for structured and unstructured data.
  • Troubleshoot and resolve issues in Hadoop jobs and database connectivity.
  • Collaborate with BI, analytics, and data science teams for data provisioning.
  • Ensure data security, governance, and compliance in all solutions.
  • Technical Skills:
  • Big Data Ecosystem:
  • Hadoop (HDFS, YARN), Hive, Spark, Sqoop, MapReduce, Oozie, Flume.
  • Databases:
  • MariaDB and/or Oracle DB (SQL, PL/SQL).
  • Programming:
  • Java, Scala, or Python for Spark/MapReduce development.
  • Data Ingestion:
  • Sqoop, Kafka, Nifi (for integrating RDBMS with Hadoop).
  • Query Optimization:
  • Hive tuning, partitioning, bucketing, indexing.
  • Tools:
  • Ambari, Cloudera Manager, Git, Jenkins.
  • OS & Scripting:
  • Linux/Unix shell scripting.
  • Soft Skills:
  • Strong analytical skills and problem-solving abilities.
  • Good communication skills for working with cross-functional teams.
  • Ability to manage priorities in a fast-paced environment.
  • Nice to Have:
  • Experience with cloud-based big data platforms (AWS EMR, Azure HDInsight, GCP Dataproc).
  • Knowledge of NoSQL databases (HBase, Cassandra).
  • Exposure to machine learning integration with Hadoop/Spark.