Cloud Engineer

Jobgether

Colombia

Presencial

COP 60.000.000 - 120.000.000

Jornada completa

Hace 3 días
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Descripción de la vacante

Jobgether in Colombia seeks a Cloud Engineer to support and scale Databricks-based data environments, onboard applications to DLZ, and build automation across Databricks and Azure resources.

You will collaborate with cross-functional teams, implement IaC with Terraform/Bicep, and optimize CI/CD pipelines, gaining deep exposure to Databricks Unity Catalog, RBAC, and Delta Sharing while driving operational improvements.

Formación

  • 1-3 years hands-on experience with Databricks.
  • 1-3 years experience with Azure Data Factory.
  • Background in application support or cloud operations.
  • Familiarity with Azure, AWS, or GCP is a plus.
  • Experience with Git repositories (GitHub/GitLab).
  • Knowledge of Unity Catalog, RBAC, Delta Sharing desirable.
  • Experience with IaC tools: Terraform, Bicep, or AWS CDK.
  • Experience with CI/CD tools: Azure DevOps, Jenkins, or GitHub Actions.

Responsabilidades

  • Provide first-level technical support for Databricks and cloud-related requests via ServiceNow.
  • Onboard new Data Landing Zones (DLZs) and gather requirements.
  • Run pipelines and scripts to provision Azure/Databricks resources.
  • Implement IaC for Azure resources and Databricks configurations.
  • Automate repetitive tasks to improve efficiency and response times.
  • Collaborate with cross-functional teams to resolve issues and improve onboarding.

Conocimientos

Databricks
Azure Data Factory
Git versioning
CI/CD pipelines
Python
PowerShell
Bash

Herramientas

Terraform
Azure DevOps
Terraform/Bicep

Descripción del empleo

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Engineer based in Colombia.

Join a technical team focused on supporting and scaling modern cloud-based data environments.
In this role, you will help application teams onboard to Databricks and build reliable Data Landing Zones (DLZ).
You will work with Azure resources, Infrastructure as Code, automation, and deployment pipelines to deliver efficient solutions.
As a first-line technical point of contact, you will troubleshoot requests and help resolve issues through structured support processes.
You will also identify opportunities to automate repetitive activities and continuously improve operational workflows.
The role combines hands-on cloud engineering with application support in a collaborative, cross-functional environment.
It is an excellent opportunity to deepen your expertise in Databricks, Azure, IaC, and cloud automation while making a direct impact on data platform operations.

Accountabilities
  • Provide first-level technical support to application teams through the ServiceNow ticketing system, investigating and resolving common Databricks and cloud-related requests.
  • Gather, clarify, and analyze technical requirements for onboarding new Data Landing Zones (DLZs).
  • Execute pipelines, scripts, and automated processes to provision, configure, or modify Azure and Databricks resources.
  • Support the deployment of commonly requested Azure resources using Infrastructure as Code (IaC) practices.
  • Identify repetitive manual activities and develop automation to improve efficiency, consistency, and support response times.
  • Collaborate with application, cloud, data, and other cross-functional teams to resolve technical issues and ensure smooth onboarding.
  • Create, maintain, and continuously improve documentation covering support procedures, workflows, configurations, and troubleshooting processes.
  • Contribute to the continuous improvement of cloud support operations and the overall Databricks environment.
Requirements:
  • 1-3 years of hands-on experience working with Databricks in a technical or operational environment.
  • 1-3 years of experience with Azure Data Factory.
  • Previous experience in application support, technical operations, cloud support, or a similar role.
  • Familiarity with major cloud platforms, particularly Azure, with exposure to AWS or GCP considered an advantage.
  • Experience using source-control systems such as Git, GitHub, or GitLab.
  • Understanding of Databricks capabilities such as Unity Catalog, role-based access control (RBAC), authentication mechanisms, and Delta Sharing is highly desirable.
  • Experience working within the Azure ecosystem and understanding of cloud resource management.
  • Familiarity with Infrastructure as Code tools such as Terraform, Bicep, or AWS CDK.
  • Experience with CI/CD pipelines and automation platforms such as Azure DevOps, Jenkins, or GitHub Actions is a plus.
  • Scripting or development experience with Python, PowerShell, Bash, or similar technologies.
  • Strong analytical and troubleshooting abilities, combined with attention to detail and a proactive approach to problem-solving.
  • Ability to communicate clearly with application teams and collaborate effectively across technical and non-technical stakeholders.
Benefits:
  • Opportunity to work hands-on with Databricks, Azure, cloud infrastructure, and modern data technologies.
  • Exposure to Infrastructure as Code, CI/CD, automation, and cloud platform operations.
  • Collaborative environment with opportunities to work closely with application and cross-functional technical teams.
  • Opportunity to develop expertise in a growing data and cloud technology ecosystem.
  • Role combining technical support, cloud engineering, automation, and continuous improvement.
  • Potential for professional growth through exposure to a broad range of cloud and data platform challenges.

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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