Big Data arxitektoru

Əsas vəzifələr

• Design and develop scalable, high-performance, and reliable data architectures for Big Data platforms
• Lead the architectural design of distributed data processing solutions using technologies such as Hadoop, Spark, and Kafka
• Design and oversee data ingestion, ETL, and real-time data processing architectures
• Define and optimize the use of relational and non-relational database technologies based on architectural requirements
• Continuously improve data architectures in terms of performance, scalability, reliability, and fault tolerance
• Ensure data governance, security, and compliance requirements are incorporated into data architecture and platform designs
• Provide technical leadership in the design and development of cloud-based data platforms
• Contribute to the integration of MLOps and DevOps practices into data platform environments
• Take an active role in the design and development of Data Warehouse and analytical data solutions
• Provide technical guidance to engineering teams and collaborate effectively with cross-functional stakeholders
• Evaluate emerging Big Data technologies and recommend improvements to existing architectures
• Drive continuous improvements to ensure the sustainability, operational efficiency, and performance of data platforms

Tələblər

• Bachelor’s degree in Computer Engineering, Computer Science, Software Engineering, or a related field
• 8-10+ years of professional experience in Big Data, Data Engineering, or Data Architecture
• Strong knowledge and hands-on experience with Big Data architectures and distributed systems
• Hands-on experience with Big Data technologies such as Hadoop, Spark, and Kafka
• Proven experience in designing high-performance, scalable, and reliable systems
• Solid knowledge of relational and non-relational database management systems
• Experience designing and implementing data ingestion frameworks and ETL processes
• Hands-on experience with real-time and stream processing frameworks
• Knowledge of Data Warehouse concepts and analytical processing technologies
• Experience with MLOps and DevOps technologies and practices
• Strong knowledge of cloud platforms and cloud-based data architectures
• Ability to optimize data architectures in terms of performance, reliability, scalability, and fault tolerance
• Knowledge of data governance, data security, and compliance within Big Data environments
• Knowledge of data visualization technologies for deriving and presenting insights from large datasets
• Experience working collaboratively with cross-functional and technical teams
• Strong ability to provide technical guidance and drive architectural decisions
• Strong analytical, problem-solving, and communication skills
• Passion for following emerging technologies and trends in the Big Data and Data Architecture ecosystem