Job Description

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.