We are seeking an experienced Big Data Engineer to design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related ecosystems. In this role you will ingest, transform, and analyze massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads. The ideal candidate combines deep Hadoop expertise with strong software engineering fundamentals and a focus on delivering reliable, high-performance, and cost-effective data platforms in production environments.

Required Qualifications: - Bachelor's degree in Computer Science, Engineering, or a related technical discipline. - 6+ years of professional experience designing and operating big-data pipelines on Hadoop. - Strong hands-on experience with Apache Spark (Scala, Python, or Java) in production environments. - Solid experience with Hive, HDFS, Sqoop, HBase, and the broader Hadoop ecosystem. - Hands-on experience with streaming data platforms such as Kafka, Spark Streaming, or Flink. - Strong SQL skills and experience with relational and NoSQL data stores. - Experience with workflow orchestration tools such as Airflow or Oozie. - Understanding of distributed systems concepts, including partitioning, replication, and fault tolerance. - Strong scripting skills in Python or Shell.

Preferred qualifications: - Experience operating Hadoop on cloud platforms such

We are seeking an experienced Big Data Engineer to design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related ecosystems. In this role you will ingest, transform, and analyze massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads. The ideal candidate combines deep Hadoop expertise with strong software engineering fundamentals and a focus on delivering reliable, high-performance, and cost-effective data platforms in production environments.

Required Qualifications: - Bachelor's degree in Computer Science, Engineering, or a related technical discipline. - 6+ years of professional experience designing and operating big-data pipelines on Hadoop. - Strong hands-on experience with Apache Spark (Scala, Python, or Java) in production environments. - Solid experience with Hive, HDFS, Sqoop, HBase, and the broader Hadoop ecosystem. - Hands-on experience with streaming data platforms such as Kafka, Spark Streaming, or Flink. - Strong SQL skills and experience with relational and NoSQL data stores. - Experience with workflow orchestration tools such as Airflow or Oozie. - Understanding of distributed systems concepts, including partitioning, replication, and fault tolerance. - Strong scripting skills in Python or Shell.

Preferred qualifications: - Experience operating Hadoop on cloud platforms such