1 month ago
Vila Nova de Gaia, Portugal +3 moreMid Level
Responsibilities
- Design, implement, and manage scalable cloud architectures in AWS.
- Build and maintain data pipelines, data systems, data warehouses, and data applications using ETL/ELT processes and schema modeling.
- Develop and maintain CI/CD pipelines for automated build, testing, and deployment.
- Implement Infrastructure as Code using Terraform, CloudFormation, or Pulumi.
- Manage and optimize Kubernetes and containerized workloads across EKS, AKS, and GKE.
- Automate operational tasks using Bash, Python, or Go.
- Monitor cloud environments using Prometheus, Grafana, ELK, CloudWatch, or Datadog.
- Apply cloud security best practices, including IAM policies, network security, and compliance frameworks.
- Collaborate with development teams to optimize cloud applications and improve DevOps workflows.
- Drive cloud cost optimization and FinOps best practices.
- Support data governance, metadata management, data quality, and compliance practices.
Requirements
- At least 4 years of experience in data engineering, including building and maintaining data pipelines, systems, and applications.
- Degree in computer science, software engineering, or an engineering domain.
- Proficiency in Python and one additional data-engineering programming or querying language such as Java, SQL, or NoSQL technologies.
- Hands-on experience with AWS and Kubernetes or container orchestration.
- Experience with data warehouse design, ETL/ELT, schema modeling, SQL and NoSQL data modeling, and distributed systems design.
- Strong CI/CD experience with tools such as Jenkins, GitHub Actions, GitLab CI/CD, or ArgoCD.
- Experience with Spark or other distributed-processing technologies and familiarity with Airflow.
- Knowledge of data governance, metadata management, data quality, compliance, cloud security, identity management, and access control.
- Advanced Infrastructure as Code knowledge using Terraform, CloudFormation, or Pulumi.
- Experience with observability and logging tools such as Prometheus, Grafana, CloudWatch, ELK, or Datadog.
- Experience with configuration-management tools such as Ansible, Chef, or Puppet.
- Familiarity with standard AI/ML processes and operations is valued.
- Fluent English is mandatory; additional language proficiency is advantageous.
- Strong communication, collaboration, analytical, problem-solving, and attention-to-detail skills.
Benefits
- Hybrid work arrangement.
- Multicultural, inclusive, and supportive team environment focused on work-life balance.
- Career-growth programs and access to training and certifications in emerging technologies.
- National and international project opportunities.
- Health and life insurance.
- Referral program with bonuses for talent recommendations.
- Access to company office locations.
Tech Stack
AnsibleApache AirflowApache SparkAWSBashChefDatadogGitHub ActionsGitLab CI/CDGoGrafanaJavaJenkinsKubernetesPrometheusPuppetPythonSQLTerraform
Categories
Data EngineeringDevOps
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.