SENIOR AWS DATA ENGINEER

at  Cubane Solutions AB

Our client is now seeking a skilled Data Engineer to join their team. This role is critical in designing, building, and maintaining our data infrastructure to ensure the integrity, accessibility, and quality of our data assets.

GOOD-TO-HAVE KNOWLEDGE OF:

AWS Cloud Management:

• Develop and enforce Identity and Access Management (IAM) policies for user and role-based access control.
• Utilize Key Management Service (KMS) for managing cryptographic keys and ensuring data encryption at rest and in transit.
• Implement and manage SSL/TLS certificates using AWS Certificate Manager (ACM) for secure communications.
• Working knowledge of ETL processes using AWS Glue for data integration and transformation.

Kubernetes (EKS):

• Create and maintain Helm charts for application deployment and configuration management.
• Implement Kubernetes best practices for resource allocation, scaling, and management.

Infrastructure as Code (IaC):

• Ensure infrastructure changes are reviewed, tested, and deployed in a controlled and automated manner.

IT Security:

• Implement and enforce security best practices across all layers of the IT infrastructure.
• Conduct or initiate regular security assessments, vulnerability scans, and penetration tests.

PREFERRED QUALIFICATIONS:

• AWS Certified Solutions Architect – Professional level preferred.
• Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD).
• Experience with continuous integration and continuous deployment (CI/CD) pipelines and tools such as Jenkins, GitLab CI, or AWS CodePipeline.

YOUR ROLE

As a Data Engineer, you will be instrumental in developing and optimizing our data pipelines and storage solutions. You will work closely with data scientists, analysts, users and other stakeholders to ensure that data is accessible, reliable, useful and efficiently processed.

KEY RESPONSIBILITIES:

• Develop and maintain scalable data pipelines and ETL processes.
• Implement and optimize data storage solutions in cloud environments (e.g., AWS, Azure, Google Cloud).
• Collaborate with data scientists and analysts to improve data processing and analysis workflows.
• Participate in data migration projects, including the transition from legacy systems to modern platforms.
• Provide support for data-related issues and assist in troubleshooting.