LocationKuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
Typefull-time
DepartmentNoresh
Company size1,001–5,000 people
PostedAug 14, 2025 · 1y ago
Verified live15h ago
At a glanceSummarised by Seekless from the posting.
Must have12
Design, develop, and maintain large-scale data processing solutions with Hadoop ecosystem
Hands-on experience with Hadoop ecosystem integration with MariaDB or Oracle DB for analytics and reporting
Experience designing and developing Hadoop-based big data solutions for batch and real-time data processing
Work with data ingestion frameworks (Sqoop, Apache Nifi, Kafka) for integrating data from MariaDB/Oracle DB into Hadoop
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
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 have3
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
Eligibility1
Ensure data security, governance, and compliance in all solutions
Skills
Hadoop
HDFS
YARN
Hive
Spark
Sqoop
MapReduce
Oozie
Flume
MariaDB
Oracle DB
SQL
PL/SQL
Java
Scala
Python
Kafka
Nifi
Ambari
Cloudera Manager
Git
Jenkins
Linux/Unix shell scripting
AWS EMR
Azure HDInsight
GCP Dataproc
HBase
Cassandra
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).