Data Engineer

Key Skills:

• Database modelling experience;
• R programming experience;
• knowledge of snowflake and/or AWS (Redshift), Azure, GCP ;
• knowledge of biomarker high dimensional (omics) data.
• Research and implement MLOps tools, frameworks and platforms for our Data Science projects.
• Work on a backlog of activities to raise MLOps maturity in the organization.
• Proactively introduce a modern, agile and automated approach to Data Science.
• Conduct internal training and presentations about MLOps tools' benefits and usage.
• Required experience and qualifications:
• Experience with Kubernetes
• Expertise in ETL and scheduling tools
• Experience in operationalization of Data Science projects (MLOps) using at least one of the popular - frameworks or platforms (e.g. Kubeflow & AWS Sagemaker).
• Good understanding of ML and AI concepts. Hands-on experience in ML model development.
• Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.
• Experience with devops, CI/CD/CT, pipelines implementation
• Experience with AWS (knowledge of other cloud providers is a plus)
• Experience with LLMOps and genAI
• Experience in running project teams
• Oracle is the Database OS, the developer needs to create/ update complex SQL queries/scripts.

Secondary Skills:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• Proven experience (5+ years) in data engineering with a strong background in software engineering.
• Very good communication skills
• Design, implement, and maintain scalable data architectures for large volumes of data in the cloud.
• Expertise in data modeling, ETL processes, and building scalable data architectures