Senior Data Engineer – Hadoop

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.
• Five or more years of professional experience designing and operating big-data pipelines on Hadoop.
• Strong hands-on expertise 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 working with both relational and NoSQL data stores.
• Experience with workflow orchestration tools such as Airflow or Oozie.
• Solid understanding of distributed systems concepts, including partitioning, replication, and fault tolerance.
• Strong scripting skills in Python or Shell.
• Excellent troubleshooting, debugging, and documentation skills.

• Experience operating Hadoop on cloud platforms such as AWS EMR, Azure HDInsight, or Databricks.
• Familiarity with modern lakehouse formats (Delta, Iceberg, Hudi).
• Exposure to data governance tooling such as Apache Atlas or Collibra.
• Experience with Kubernetes-based data platforms (Spark-on-K8s, Trino).
• Hands-on experience with CI/CD and infrastructure-as-code in data engineering workflows.

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