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.