Data Engineer

Master-Works; Saudi Arabia; On-site; SAR 120,000 - 150,000; Full time

Job summary

A technology company in Saudi Arabia is seeking an experienced Data Engineer to manage data collection, integration, and processing tasks. The ideal candidate should have 5+ years of experience and be proficient with big data technologies, ETL processes, and cloud computing. This position involves working on large-scale data solutions and requires strong analytical skills.

Qualifications

• Preferably 5+ years of experience in data engineering.
• Understanding of big data technologies is essential.
• Experience with NoSQL and relational databases.

Responsibilities

• Collect data from various sources including APIs and databases.
• Design and implement efficient data pipelines.
• Manage and optimize data storage and performance.
• Develop ETL processes for data transformation.
• Work with big data technologies for data analysis.
• Leverage cloud platforms for data solutions.
• Understand distributed systems for data volume handling.
• Implement real-time data processing with streaming tools.

Skills

Data Collection

Data Integration

ETL Processes

Big Data Technologies

NoSQL Databases

Cloud Computing

Distributed Systems

Streaming Data Processing

Job description

Overview

Nationality: Any Arabic Nationality to achieve better communication and understand our Arabic data content better.

Responsibilities

• Data Collection and Integration: Data engineers collect data from various sources, including databases, APIs, external data providers, and streaming sources. They must design and implement efficient data pipelines to ensure a smooth flow of information into the data warehouse or storage system.
• Data Storage and Management: Once the data is collected, data engineers are responsible for its storage and management. This involves choosing appropriate database systems, optimizing data schemas, and ensuring data quality and integrity. They also must consider scalability and performance to handle large volumes of data.
• ETL (Extract, Transform, Load) Processes: ETL is a fundamental process in data engineering. Data engineers design ETL pipelines to transform raw data into a format suitable for analysis. This involves data cleansing, aggregation, and enrichment, ensuring the data is usable for data scientists and analysts.
• Big Data Technologies: In todays data landscape, dealing with big data is the norm rather than the exception. Data engineers work with big data technologies such as Hadoop and Spark to efficiently process and analyze massive datasets.
• NoSQL Databases: In addition to traditional relational databases, data engineers often work with NoSQL databases like MongoDB and Cassandra, which are well-suited for handling unstructured or semi-structured data.
• Cloud Computing: Cloud platforms like AWS, Azure, and Google Cloud have become the backbone of modern data infrastructure. Data engineers leverage these platforms to build scalable and cost-effective data solutions.
• Distributed Systems: Data engineering often involves distributed systems architecture to handle huge data volumes and ensure fault tolerance. Understanding how distributed systems work is essential for data engineers.
• Streaming Data: Real-time data processing is crucial in many industries. Data engineers work with streaming technologies like Apache Kafka to handle and analyze data as it flows in.

Qualifications

preferably 5+ years of experience.