Data Engineer med blik for skyen

This Data Engineer role focuses on designing, building, and maintaining scalable data pipelines and architectures with an emphasis on cloud technologies. The ideal candidate should have strong expertise in cloud platforms such as AWS, Azure, or Google Cloud, enabling efficient data storage, processing, and integration in cloud environments. Proficiency in programming languages commonly used in data engineering, such as Python, SQL, and possibly Scala or Java, is essential for developing data workflows and automation scripts. Experience with distributed data processing frameworks like Apache Spark or Hadoop is valuable for handling large-scale datasets. Familiarity with data warehousing solutions, ETL/ELT processes, and real-time data streaming tools such as Kafka or AWS Kinesis is important to ensure seamless data ingestion and transformation. Knowledge of containerization and orchestration technologies like Docker and Kubernetes may be beneficial for deploying and managing data services in the cloud. The role requires understanding of data modeling, database systems (both relational and NoSQL), and best practices in data governance, security, and compliance to maintain data quality and privacy. Strong analytical skills and problem-solving abilities are necessary to optimize data workflows and support data-driven decision-making. While specific experience and education levels are not provided, candidates with a background in computer science, engineering, or related fields, combined with hands-on experience in cloud-based data engineering projects, would be well-suited for this position.