Your Mission as a Big Data Engineer at Zarrin Roya is to design, develop, and maintain distributed systems for processing large-scale datasets. Also you will be responsible to build a reliable, scalable, and efficient data infrastructure that empowers our teams to access data and run complex analytics in real-time. Key Responsibilities:Build and maintain scalable ETL pipelines for batch and real-time data processing.Design and implement distributed SQL query engines using Trino and Apache Spark for large-scale data analytics.Optimize data processing workflows and ensure real-time querying and analytics.Work with data storage systems like Apache Iceberg, MinIO, and Ceph to ensure efficient data management and accessibility.Collaborate with data scientists and analysts to deliver solutions for data modeling, data transformation, and real-time analytics.Troubleshoot and optimize the performance of distributed data systems to meet SLA requirements.Skillset: Proficiency in Python or Scala for building data processing systems.Experience with Apache Kafka or Redpanda for streaming data pipelines.Solid understanding of Trino and Apache Spark for distributed SQL-based querying and real-time data processing.Hands-on experience with Apache Iceberg for managing versioned data lakes.Familiarity with object storage solutions like MinIO and Ceph for self-hosted environments.Experience with ClickHouse or other OLAP systems for high-performance analytics.Knowledge of data orchestration tools like Apache Airflow and dbt for managing workflows.Strong problem-solving, analytical thinking and Effective communication skills

Your Mission as a Big Data Engineer at Zarrin Roya is to design, develop, and maintain distributed systems for processing large-scale datasets. Also you will be responsible to build a reliable, scalable, and efficient data infrastructure that empowers our teams to access data and run complex analytics in real-time. 
Key Responsibilities:
Build and maintain scalable ETL pipelines for batch and real-time data processing.
Design and implement distributed SQL query engines using Trino and Apache Spark for large-scale data analytics.
Optimize data processing workflows and ensure real-time querying and analytics.
Work with data storage systems like Apache Iceberg, MinIO, and Ceph to ensure efficient data management and accessibility.
Collaborate with data scientists and analysts to deliver solutions for data modeling, data transformation, and real-time analytics.
Troubleshoot and optimize the performance of distributed data systems to meet SLA requirements.
Skillset: 
Proficiency in Python or Scala for building data processing systems.
Experience with Apache Kafka or Redpanda for streaming data pipelines.
Solid understanding of Trino and Apache Spark for distributed SQL-based querying and real-time data processing.
Hands-on experience with Apache Iceberg for managing versioned data lakes.
Familiarity with object storage solutions like MinIO and Ceph for self-hosted environments.
Experience with ClickHouse or other OLAP systems for high-performance analytics.
Knowledge of data orchestration tools like Apache Airflow and dbt for managing workflows.
Strong problem-solving, analytical thinking and Effective communication skills