Big Data Architect

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