Senior Data Engineer - Big Data/ Hadoop Ecosystem

Job Title: Senior Data Engineer - Big Data/ Hadoop Ecosystem Job Type: Full-time Location: On-site Dubai, Dubai, United Arab Emirates Overview Join our team as a Senior Data Engineer - Big Data/ Hadoop Ecosystem, where you will take the technical lead on pioneering data initiatives within the banking sector. Leveraging your expertise in the Hadoop ecosystem, you will architect, build, and optimize large-scale data systems while mentoring a talented team of data engineers. If you thrive in highly collaborative, asynchronous environments and are passionate about delivering robust data solutions, this role is for you.Responsibilities Design, develop, and optimize scalable data processing systems using the Hadoop ecosystem (HDFS, Map Reduce, Hive, Pig, HBase, Flume, Sqoop) and other Big Data technologies.Lead, mentor, and inspire a team of data engineers, ensuring timely and high-quality project delivery.Engineer, tune, and maintain complex data pipelines in Java, Map Reduce, Hive, and Spark, including implementing stream-processing with Spark-Streaming.Design and build efficient dimensional data models and scalable architectures to empower analytics and business intelligence.Oversee data integrity analysis, deployment, validation, and auditing of data models for accuracy and operational excellence.Leverage advanced SQL skills for performance tuning and optimization of data jobs.Collaborate with business intelligence teams to deliver industry-leading dashboards and data products.Qualifications10+ years of hands-on experience as a Big Data Engineer, with deep technical expertise in the Hadoop ecosystem (Cloudera preferred), Apache Spark, and distributed data frameworks.Proven experience leading backend/distributed data systems teams while remaining technically hands-on.Advanced proficiency in Java for Map Reduce development, as well as strong skills in Python and/or Scala.Expertise in Big Data querying tools including Hive, Pig, and Impala.Strong experience with both relational (Postgres) and No SQL databases (Cassandra, HBase).Solid understanding of dimensional data modeling and data warehousing principles.Proficient in Linux/Unix systems and shell scripting.Preferred Qualifications Experience with Azure cloud services (Azure Data Lake, Databricks, HDInsight).Knowledge of stream-processing frameworks such as Spark-Streaming or Storm.Background in Financial Services or Banking industry, with exposure to data science and machine learning tools. #J-18808-Ljbffr