Big Data Hadoop Developer

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