Mid-Level DevOps Engineer Data Lake Project

Objectives of this position

The objective of the position is to maintain and optimize a fully automated GitOps-driven cloud infrastructure. Act as a highly resolutive self-driven operational backup in the absence of the DevOps & Cloud Manager keeping production systems stable and secure with minimal supervision.

What will you do

Maintain Code-Driven Infrastructure: Maintain and scale declarative Infrastructure as Code (IaC) solutions via Terraform across complex large-scale codebases prioritizing reusable module design state optimization and drift prevention.

Manage Automated Workflows & GitOps: Oversee the end-to-end lifecycle of Kubernetes clusters using GitOps practices (ArgoCD) and manage automated infrastructure workflows ensuring zero manual intervention in the deployment pipeline.

Autonomous Incident Resolution: Drive technical incidents to resolution with a high degree of autonomy performing deep root-cause analysis and utilizing automated monitoring/alerting frameworks to proactively maintain system health.

Enforce Rigorous Quality Standards: Ensure all infrastructure code automated workflows and configurations meet strict quality gates. Author and maintain comprehensive crystal-clear technical documentation for all architectures and automation processes.

Support Data & AI Automation: Maintain the automated provisioning and scaling of infrastructure for Data and AI workloads including GPU-enabled Kubernetes nodes and cloud-native AI pipeline components.

Enterprise SaaS Administration: Programmatically configure and manage enterprise platforms including Bitbucket Cloud (RBAC branch strategies) and SonarQube Cloud (Quality Gates).

Contribute to Future Migrations: Participate actively in the long-term planning and execution of our multi-year strategic migration from Azure to Google Cloud Platform (GCP) and from Argo Workflows to Azure DevOps pipelines.

What will you need

Background: Degree holder in Computer Science Software Engineering or a closely related field (or 35 years of equivalent commercial experience in a SysAdmin/DevOps discipline).

Experience Tier: 35 years of commercial experience working as a DevOps Engineer in highly automated multi-contributor enterprise environments.

Automation Workflow & GitOps Depth: Solid understanding of event-driven automation workflows and extensive hands-on experience running Kubernetes workloads using GitOps tools (ArgoCD or equivalent).

Large-Scale IaC: Proven experience handling Terraform inside large repositories including clean state management and writing modular linted reusable code.

Cloud Platforms: 2 years of administrative experience with Microsoft Azure cloud services. Familiarity with Google Cloud Platform (GCP) or Azure DevOps is a strong plus due to upcoming migration initiatives.

Containerization & Code Quality: Strong proficiency in Docker (creating secure unprivileged size-optimized containers) and familiarity with running code quality automation tools (like SonarQube).

Mindset: Highly resolutive problem-solver who takes strict ownership of tasks and thrives in an environment that requires minimal micromanagement.

Development opportunities:

Gain deep exposure to enterprise-scale multi-cloud migrations and modern AI infrastructure engineering. Learn new tools through hands-on proof-of-concept projects.

Required Skills:

Mid-Level DevOps Engineer: Data Lake Project

Required Education:

degree / diploma

Employment Type : Full Time
Experience: years
Vacancy: 1
Monthly Salary Salary: 45000 - 60000