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Brasil beBeeDataGovernance Tempo inteiroCloud Engineer We are seeking a highly skilled Cloud Engineer to join our team. The ideal candidate will have expertise in Azure DevOps pipelines, Git repositories, and artifact management. Terraform infrastructure-as-code solutions Azure Data Lake Storage Gen2 hierarchical namespace ACL models for data governance As a Cloud Engineer, you will play a key...
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Cloud Engineer
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Índio do Brasil GeorgiaTEK Systems Inc. Tempo inteiroTitle: Cloud Engineer Location: Remote / Hybrid (BRAZIL) Experience Level: Mid–Senior Duration: Long-term Contract Key Responsibilities: - Design, implement, and support solutions on GCP and AWS - Develop and maintain automation scripts using Python - Lead or support workflow migration initiatives to cloud-native architectures - Work with AVID MAM for...
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Vitória Brasil Matchpoint Tempo inteiroCloud Engineer (Azure)Location: Remote (EST Hours)Contract Duration: 12 months (with possible extension for ongoing needs)Experience requiredMust have ***** communication and ability to articulate well.Azure infrastructure.*Automation via BICEPOverview:We are seeking a Cloud Engineer with strong expertise in Azure to support our evolving cloud infrastructure...
Cloud engineer
Há 1 mês
Sr Cloud Engineer (São Paulo, Brazil) Join a community of experts in Information Digital Engineering (IDE), driving ideas to reality by embedding AI across the organization—from optimizing existing operations to accelerating the development of next-generation clean energy solutions. The IDE team creates business value daily through cutting-edge knowledge, maximizing value from information and data using deep technical expertise and market-leading tools to deliver actionable, data-driven insights. Your Day As a Senior Cloud Engineer, you are a subject matter expert—curious, innovative, and strategic. You will design, deploy, manage, and optimize scalable, secure, and cost-effective cloud infrastructure and services. You'll convert vision and data strategy into IT solutions and foster data-driven thinking across the organization. Key Responsibilities: Communicate effectively with technical developers and business managers, earning trust and respect. Lead roll-out and embedding of Data Foundation initiatives using market-standard tools. Coordinate change management, incident management, and problem resolution processes. Ensure traceability of requirements from data through testing, training, and transition. Drive implementation efficiency across pilots and future projects to minimize cost and maximize value. Team Culture You'll bring deep technical skills and become a key contributor to projects defining the data journey. Expect continuous learning and collaboration across companywide teams to stay future-ready. Education & Experience University degree in any IT discipline Minimum 5+ years of experience in the IT industry ️ Expected Skills Build and operate resilient, scalable cloud platforms (Iaa S, Paa S, cloud-native) on Azure Implement CI/CD pipelines, infrastructure as code, monitoring, logging, and incident response Enforce security, compliance, cost governance, and performance optimization Collaborate with engineers, developers, security, and SRE teams to define standards and best practices Lead migration and modernization initiatives with robust testing and rollback plans Mentor junior engineers and contribute to architectural decisions Proficient in Terraform, Cloud Formation, ARM templates, Python, Bash, Power Shell Experience with Kubernetes, Docker, microservices, service meshes, disaster recovery, and backup Leadership Skills Self-motivated and innovative, with a drive to initiate and close projects Skilled communicator with technical and business stakeholders Strong understanding of data foundation: modeling, quality, governance, maturity, and strategy Experience with source control (Git Hub, Azure Dev Ops) Familiarity with AGILE and KANBAN methodologies Nice to Have Knowledge of Gas/Power Trading (CCGT, Wind, Solar, Battery) Risk modeling and management Quantitative/statistical analysis for data insights Commodity modeling (energy, environmental products, meteorology) CI/CD pipeline creation/enhancement Scripting: YAML, Power Shell, Terraform Big data tools: Kafka, Hadoop, Spark; stream-processing systems Workflow tools: Azkaban, Luigi, Airflow Python libraries: Num Py, Pandas, Django Azure certification