Data Engineer

3 days ago

Dubai, India MM Staffing & Career Consultants Full time  19,000 -  60,000 per year


Job Description:

Work Location : Dubai

Budget : AED 19,000 (Maximum)

Notice Period :  Early joiners preferred (Maximum 30 days)

Job Description:

We are looking for a highly skilled and motivated Spark Data Engineer to join our team. The ideal candidate will have a strong background in Apache Spark, data ingestion, data processing, and data integration, and will be responsible for developing and maintaining our dynamic data ingestion framework using the Spark framework. The candidate should have expertise in building scalable, high-performance, and fault-tolerant data processing pipelines using Spark, and be able to optimize Spark jobs for performance and scalability. The candidate should also have experience in designing and implementing data models, handling data errors, implementing data quality and validation processes, and integrating Spark applications with other big data technologies in the Hadoop ecosystem.

Responsibilities:

Develop and maintain a dynamic data ingestion framework using Apache SparkImplement data ingestion pipelines for batch processing and real-time streaming using Spark's data ingestion APIsDesign and implement data models using Spark's DataFrame and Dataset APIsOptimize Spark jobs for performance and scalability, including caching, broadcasting, and data partitioning techniquesImplement error handling and fault tolerance mechanisms to handle data errors, processing failures, and system failures in Spark applicationsImplement data quality and validation processes, including data profiling, data cleansing, and data validation rules using Spark's data processing and data validation APIsIntegrate Spark applications with other big data technologies in the Hadoop ecosystem, such as Hadoop, Hive, HBase, Kafka, and othersEnsure data security by implementing data encryption, data masking, and data access controls in Spark applicationsUse version control systems, such as Git, for source code management, and implement DevOps practices, such as continuous integration, continuous delivery, and automated deployments, in Spark application development workflows

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Engineering, or a related fieldStrong proficiency in Apache Spark, including Spark Core, Spark SQL, Spark Streaming, and Spark MLlib, with multiple production developments and deployment experience.Proficiency in either Scala or Python programming languages, with knowledge of functional programming conceptsExperience in developing and maintaining dynamic data ingestion frameworks using SparkExperience in data processing, data integration, and data modeling using Spark's DataFrame and Dataset APIsKnowledge of performance optimization techniques in Spark, including caching, broadcasting, and data partitioningExperience in implementing error handling and fault tolerance mechanisms in Spark applicationsKnowledge of data quality and validation techniques using Spark's data processing and data validation APIsFamiliarity with other big data technologies in the Hadoop ecosystem, such as Hadoop, Hive, HBase, Kafka, etc.Experience in implementing data security measures in Spark applications, such as data encryption, data masking, and data access controlsStrong problem-solving skills and ability to troubleshoot and resolve issues related to Spark applicationsProficiency in using version control systems, such as Git, and implementing DevOps practices in Spark application development workflowsExcellent communication and collaboration skills, with the ability to work effectively in a team-oriented environment

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