Big Data Hadoop Developer
Unison Group Open · verified Oct 24, 2026 At a glance
Mid-level Data Engineering role at Unison Group. Kuala Lumpur · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and tune Hadoop solutions for both scheduled batch work and real-time data processing
- Bring MariaDB or Oracle data into Hadoop through ingestion tools such as Sqoop, Nifi or Kafka
- Develop Hive, Spark and MapReduce jobs that reshape data for analysis
- Improve Hive queries, Spark workloads and HDFS use, while maintaining ETL flows for structured and unstructured data
- Resolve job and database connection failures, support data access for analytics teams, and apply security and governance controls
What you bring
- Hands-on capability with Hadoop and its ecosystem, including distributed storage and processing tools
- Experience connecting MariaDB or Oracle databases with Hadoop, using SQL or PL/SQL
- Programming ability in Java, Scala or Python for Spark or MapReduce development
- Linux or Unix shell scripting skills and familiarity with Hadoop query tuning
Who this fits
This onsite role in Kuala Lumpur suits a mid-level developer who can build and troubleshoot Hadoop data workflows. You'll work with BI, analytics and data science teams, so clear communication and managing competing priorities matter.
From the employer
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.
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