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Lead DevOps Engineer

* Salário: R$ 18.000 a R$ 30.000 por mês (estimado)

* O valor exibido é uma estimativa calculada com base em dados públicos e referências do mercado. Não garantimos que este seja o salário oferecido para esta vaga específica.

Área: Tecnologia da Informação

Nível: Gerente

We are searching for a Lead DevOps Engineer to join our Ads Organization, where you will be instrumental in supporting the reliability and scalability of our data infrastructure. This position emphasizes upgrading systems, resolving technical challenges, optimizing CI/CD pipelines, and partnering with stakeholders to deliver robust solutions in a data-driven setting.

Responsibilities

  • Lead and optimize data processing operations using Airflow/MWAA, Spark, and Flink
  • Design and maintain cloud infrastructure with AWS, Kubernetes, and Terraform
  • Work alongside stakeholders to gather requirements and share updates on infrastructure changes
  • Execute upgrades, perform maintenance, and troubleshoot data platforms, leveraging Datadog for system monitoring and performance insights
  • Enhance CI/CD pipelines with Spinnaker and Jenkins to ensure efficient and consistent application delivery

Requirements

  • Minimum 5 years of experience in a DevOps engineering role
  • At least one year of experience in a leadership or team management capacity
  • Strong background with Amazon Web Services (AWS) for cloud infrastructure deployment and management
  • Hands-on experience with Apache Airflow for orchestrating and scheduling data workflows
  • Advanced knowledge of Kubernetes for managing and scaling containerized applications
  • Skilled in using Terraform for infrastructure automation and configuration
  • Proficient English communication skills at B2 level or higher for effective collaboration and reporting

Nice to have

  • Experience with Apache Flink for processing real-time data streams
  • Familiarity with Apache NiFi for automating and controlling data flows
  • Knowledge of Databricks for advanced analytics and machine learning projects
  • Experience with Datadog for infrastructure monitoring and issue resolution