[Job-19347] Mid-Level DevOps Engineer (AWS), Brazil

As a Mid-Level DevOps Engineer at CI&T, your primary responsibilities will include managing and optimizing a variety of AWS services, including Kinesis Data Streams and Lambda, for data infrastructure. You'll utilize Python for automation and data processing, engage with SQL or Snowflake for data storage and transformation, and support data visualization projects. Additionally, you'll work with source control systems, such as Git and GitHub, and CI/CD tools like Jenkins.

CI&T requires candidates for the Mid-Level DevOps Engineer position to have at least 2 years of experience in DevOps or SRE roles, specifically focusing on AWS and Python. Proficiency in data tools like Snowflake or high-level SQL is essential. Familiarity with dbt for data transformation, experience with CI systems like Jenkins, and strong communication skills are additional advantages.

CI&T places a strong emphasis on professional development for all employees, including Mid-Level DevOps Engineers. We provide access to CI&T University, partnerships with online learning platforms, and various training courses to foster continuous learning. We encourage our team members to enhance their skills and grow within the company, benefiting both personal and professional development.

For the Mid-Level DevOps Engineer role at CI&T, soft skills are as important as technical expertise. We value excellent problem-solving abilities, strong analytical and troubleshooting capabilities, and effective communication skills. Being able to articulate complex concepts to non-technical stakeholders and collaborate effectively within teams are integral to success in this role.

CI&T offers a comprehensive benefits package for Mid-Level DevOps Engineers, including health and dental plans, meal allowances, childcare assistance, gym memberships, life insurance, and access to mental health support. Additionally, we provide extensive resources for personal and professional growth, including online courses and discounts on various services.

When discussing your experience with AWS services, be specific about the services you have utilized, such as Kinesis, Lambda, or CloudWatch. Share examples of projects where you effectively managed these services to deliver results. Highlight how your contributions led to optimized operations or improved performance, demonstrating your hands-on experience and problem-solving abilities.

To ensure effective collaboration, I prioritize open communication and maintain transparency about progress and challenges. Utilizing collaborative tools like Jira and Slack for project tracking and regular check-ins helps align our objectives. I also advocate for a culture of feedback and continuous improvement, where team members feel comfortable discussing their ideas and concerns.

In automating infrastructure management with Python, I first identify repetitive tasks that can be automated, such as deploying resources or managing configurations. Then, I leverage libraries like Boto3 to interact with AWS APIs and write scripts that execute those tasks efficiently. I emphasize testing and documentation to ensure that the scripts are robust and maintainable.

My experience with dbt involves transforming data workflows from raw data ingestion to optimized datasets ready for analysis. I typically create models to define transformations and leverage tests to ensure data quality. Discussing a specific project where I utilized dbt to enhance data pipelines will showcase my understanding of data best practices.

When troubleshooting CI/CD pipeline issues, I follow a systematic approach: first, I gather logs and analyze error messages to pinpoint the issue. Then, I reproduce the error in a controlled environment for further diagnosis. I also review recent changes to identify potential causes. Once I understand the root cause, I implement a solution and document the process for future reference.

In a previous role, I faced challenges with scaling our infrastructure to handle increased traffic during peak periods. I implemented auto-scaling policies and optimized load balancing for our AWS services. This experience taught me a lot about resource management and handling real-time traffic demands effectively.

To maintain data security in cloud environments, I adhere to best practices such as restricting access with IAM roles, employing encryption for data at rest and in transit, and regularly reviewing security groups and policies. Additionally, conducting periodic audits helps to uncover and rectify vulnerabilities proactively, ensuring a secure environment.

I stay current with DevOps technologies by actively participating in industry meetups, webinars, and online courses. I follow relevant tech blogs, engage in forums, and contribute to open-source projects to deepen my understanding. Networking with peers in the industry also helps me keep abreast of emerging trends and best practices.

I prefer using Git and GitHub for source control due to their widespread adoption and robust features like branching and pull requests that facilitate collaboration. The integration capabilities with CI/CD tools further enhance workflow efficiency, making tracking changes and managing code a seamless process.

When implementing monitoring for a new application service, I start by identifying key metrics to track, such as performance, error rates, and user engagement. I configure monitoring tools like CloudWatch to collect and visualize these metrics. Setting up alerts for anomalies ensures that I can respond swiftly to issues impacting service performance.