Senior Specialist Data Engineering📣 إعلان

About Qiddiya and the Role

Qiddiya is seeking a Senior Specialist Data Engineering to join its team in Riyadh, Saudi Arabia. This full-time position requires 5-10 years of relevant experience in data engineering. The successful candidate will play a crucial role in transforming raw data into useful data systems, supporting analytics and decision-making processes across the organization.

Role Purpose

The Senior Specialist Data Engineering will collaborate closely with cross-functional teams to ensure the availability, reliability, and accessibility of data for various business functions. A primary objective of this role is to enhance operational efficiency by aligning data systems with strategic business goals. This position requires strong analytical skills and the ability to integrate data from diverse sources effectively.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes using tools such as Apache Spark, Apache Kafka, and Apache Airflow to ingest, process, and transform large volumes of data from various sources.
• Deploy Data Pipelines on different Data Processing Products, including DataFlow (Apache Beam), DataProc (Hadoop/Spark), Data Fusion, and Cloud Composer (Airflow).
• Build distributed systems and data stores.
• Collaborate with and support data science, marketing, and customer success teams in data acquisition and tool integration.
• Configure Google Cloud Platform services.
• Implement and optimize data storage solutions, including data warehouses (*, Amazon Redshift, Google BigQuery), data lakes (*, AWS S3, Azure Data Lake Storage), and NoSQL databases (*, MongoDB, Cassandra).
• Work closely with data architects to design and implement efficient data models using dimensional modeling techniques (*, star schema, snowflake schema) that support business requirements and enable effective data analysis.
• Collaborate with data scientists and analysts to understand data requirements and develop solutions to support advanced analytics and machine learning initiatives, including model training and deployment.
• Implement data quality checks, monitoring, and custom scripts to ensure the accuracy, completeness, and reliability of data.
• Participate in troubleshooting and resolving data-related issues, ensuring timely resolution and minimal disruption to business operations.
• Stay updated on emerging technologies and best practices in data engineering, including cloud-native solutions and serverless architectures, and contribute to the continuous improvement of data platforms and infrastructure.
• Propose and implement automation for repetitive tasks.
• Provide support for development teams in deployment-related topics.
• Modernize data lakes and data warehouses.

Required Qualifications

• Bachelor's degree in Computer Science, IT, or a similar field; a Master's degree is a plus.
• Previous experience as a data engineer or in a similar role, with a preference for Google Cloud Platform experience.
• Strong understanding of data modeling, ETL processes, data warehousing concepts, and data integration techniques.
• Excellent problem-solving skills and attention to detail, with the ability to work effectively in a fast-paced environment and manage multiple priorities.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.
• Data engineering cloud certification (*, Google Certified Data Engineer) is a plus.

Technical Expertise

• Technical expertise with data models, data mining, and segmentation techniques.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with SQL and NoSQL databases.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and familiarity with related services (*, AWS Glue, Azure Data Factory, Google BigQuery).
• Solid knowledge of Google's BigQuery for effective data processing.

Work Environment

This is a full-time position based in Riyadh, Saudi Arabia, within a dynamic and collaborative environment. The role involves working with diverse teams and staying abreast of the latest advancements in data engineering technologies.