Big Data Engineer | Spark, Hadoop, Kafka | Visa

Müller`s Solutions; Dubai; On-site; AED 250,000 - 420,000; Full time

Benefits offered by this job

Attractive Package

Family Benefits

Visa

Air Tickets

Job summary

Müller’s Solutions in Dubai is seeking an experienced Big Data Engineer to design and develop scalable data solutions that enable advanced analytics and insights across the organization. You will work with large data sets and cutting-edge technologies to ensure data processing is efficient and reliable.

You will build data pipelines with Spark, Hadoop, and Kafka; collaborate with data scientists, analysts, and IT; ensure data quality; optimize storage; monitor workflows; and document

Qualifications

• Bachelor's degree or higher in CS/IT or related field.
• 3+ years of experience as a Big Data Engineer or similar.
• Proficiency with Spark, Hadoop, Kafka, and data processing frameworks.

Responsibilities

• Design, build, and maintain scalable data pipelines using Spark, Hadoop and Kafka.
• Collaborate with data scientists, analysts and IT to define data requirements.
• Ensure high data quality and integrity with validation and testing processes.
• Optimize data storage for performance and cost across cloud and on-prem environments.
• Monitor and troubleshoot data processing workflows to ensure timely delivery.
• Document data architectures, processes and workflows for knowledge sharing and compliance.

Skills

Big Data Technologies

Java/Scala/Python

ETL tools

Cloud platforms (AWS/Azure/GCP)

Data quality

Communication

Education

Bachelor's degree in Computer Science, Information Technology, or related field

Tools

Apache Spark

Hadoop

Apache Kafka

Docker/Kubernetes

Job description

Müller’s Solutions in Dubai is seeking an experienced Big Data Engineer to design and develop scalable data solutions that enable advanced analytics and insights across the organization. You will work with large data sets and cutting-edge technologies to ensure data processing is efficient and reliable.

You will build data pipelines with Spark, Hadoop, and Kafka; collaborate with data scientists, analysts, and IT; ensure data quality; optimize storage; monitor workflows; and document