1409 – Manager, Cloud Engineer – AI and Automation

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Our client is seeking a highly skilled and experienced Cloud Engineer to join their team. In this role, you will be responsible for designing, implementing, and maintaining their cloud infrastructure. You will work closely with their development and operations teams to ensure the reliability, scalability, and security of their cloud-based services.

ROLE RESPONSIBILITIES

• Design and Implement Cloud Solutions: Develop and deploy scalable, reliable, and secure cloud architectures using industry best practices.
• Infrastructure Management: Maintain and manage cloud environments, ensuring optimal performance and cost-efficiency.
• Automation: Develop automation scripts to streamline deployment, management, and monitoring of cloud resources.
• Security: Implement and enforce security best practices to safeguard their cloud infrastructure and data.
• Collaboration: Work closely with development, operations, and security teams to ensure seamless integration and continuous improvement of their cloud services.
• Troubleshooting: Identify and resolve technical issues related to cloud infrastructure and services.
• Documentation: Maintain comprehensive documentation of cloud infrastructure, configurations, and processes.
• Stay Current: Continuously research and stay up-to-date with the latest trends and advancements in cloud technology.

BASIC QUALIFICATIONS

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Minimum of 5 years of experience in cloud engineering or a similar role.
• Proficiency with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of cloud architecture principles and best practices.
• Experience with infrastructure-as-code tools such as Terraform or Cloud Formation.
• Proficiency in scripting languages like Python, Bash, or PowerShell.
• Proficiency in scripting Airflow DAGs
• Solid understanding of networking concepts and protocols.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Strong problem-solving and troubleshooting skills.
• Excellent communication and teamwork abilities.

PREFERRED QUALIFICATIONS

• Programming Languages: Proficiency in Python, SQL, and familiarity with Java or Scala.
• Data Warehousing: Experience with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake.
• ETL Tools: Knowledge of ETL tools like Apache NiFi, Talend, or Informatica.
• Big Data Technologies: Familiarity with Hadoop, Spark, and Kafka for big data processing.
• Cloud Platforms: Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Containerization: Understanding of Docker and Kubernetes for containerization and orchestration.
• AI and Automation: Knowledge of AI-driven tools for data pipeline automation, such as Apache Airflow or Prefect. Ability to use GenAI or Agents to augment data engineering practices
• Data Integration: Skills in integrating data from various sources, including APIs, databases, and external files.
• Data Modeling: Understanding of data modeling and database design principles, including graph technologies like Neo4j or Amazon Neptune.
• Structured Data: Proficiency in handling structured data from relational databases, data warehouses, and spreadsheets.
• Unstructured Data: Experience with unstructured data sources such as text, images, and log files, and tools like Apache Solr or Elasticsearch.
• Data Excellence: Familiarity with data excellence concepts, including data governance, data quality management, and data stewardship.

Please apply by sending your CV and a motivational letter in English.

Work Location Assignment: Hybrid