Big Data Engineer - Hybrid - Officer

Big Data Engineer - Hybrid - Officer

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Job Overview

Responsible for designing, developing, and optimizing data processing solutions using a combination of Big Data technologies. Focus on building scalable and efficient data pipelines for handling large datasets and enabling batch & real-time data streaming and processing. Responsibilities include: developing Spark applications using Scala or Python (Pyspark) for data transformation, aggregation, and analysis; developing and maintaining Kafka-based data pipelines; creating and optimizing Spark applications using Scala and PySpark; integrating Kafka with Spark for real-time processing; collaborating with data teams; tuning and optimizing Spark and Kafka clusters; writing clean, functional, and optimized code; troubleshooting and resolving issues; maintaining documentation; and staying updated on technology trends. Proficiency in Hadoop ecosystem big data tech stack (HDFS, YARN, MapReduce, Hive, Impala), Spark (Scala, Python) for data processing and analysis, Kafka for real-time data ingestion and processing, ETL processes and data ingestion tools, deep hands-on expertise in Pyspark, Scala, Kafka, programming languages (Scala, Python, or Java for developing Spark applications, SQL for data querying and analysis), data warehousing concepts, Linux/Unix operating systems, problem-solving and analytical skills, and version control systems.

Technology: Applications Development

Time Type: Full time

Most Relevant Skills: Please see the requirements listed above.

Other Relevant Skills: For complementary skills, please see above and/or contact the recruiter.

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