Senior DevOps Engineer

ERGO Technology & Services S.A.

Gdańsk +1 more
hybrid
☁️ Azure DevOps
hybrid
🔄 DevOps
Infrastructure as Code
Terraform
☁️ PowerShell/ARM Templates Azure DevOps (Build Pipelines
Release Pipelines)
Ansible
☁️ Azure Policies
☁️ Azure Data Factory
☁️ Azure Kubernetes Services
☁️ Azure Databricks
☁️ Azure Event Hub
☁️ Azure SQL Server
☁️ Azure Data Lake Store
☁️ Azure Blob Storage
Power BI
☁️ Azure Search
☁️ Azure Cosmos DB
☁️ Azure DSVM (Windows & Linux)
☁️ Azure ML
☁️ Azure Networking
☁️ Azure AD
☁️ Azure Active Directory Domain Services
📊 Dataiku

Requirements

Expected technologies

Azure DevOps

Optional technologies

Dataiku

Operating system

Windows

Linux

Our requirements

  • fluency in English
  • several years of experience in complex Azure environments
  • exceptional skills in Infrastructure as Code (IaC) development using Terraform/PowerShell/ARM Templates, Azure DevOps (Build Pipelines, Release Pipelines), Ansible, and Azure Policies
  • being proficient in multiple Azure technologies, including Azure Data Factory, Azure Kubernetes Services, Azure Databricks, Azure Event Hub, Azure SQL Server, Azure Data Lake Store, Azure Blob Storage, Power BI, Azure Search, Azure Cosmos DB, Azure DSVM (Windows & Linux), and Azure ML, specifically with regard to deployment and configuration
  • robust Azure networking skills, including VNets, Hub & Spoke architectures, and connectivity between Azure and on-premises
  • good understanding of Azure AD, Azure Active Directory Domain Services, and integration of various Azure technologies in accordance with IT security requirements
  • high level of commitment and flexibility regarding task assignment, coupled with a willingness to tackle a variety of complex tasks

Optional

  • fluency in German
  • proficient skills in Dataiku

Your responsibilities

  • managing deployment automation of Azure PaaS/SaaS services within the context of a Big Data&Analytics platform
  • carrying out automation of configuration validation and re-establishment to comply with IT security requirements and ensure platform stability
  • implementing end-to-end solution automation for the complete Machine Learning (ML) lifecycle
Views: 3
Published18 days ago
Expiresin 23 days
Work modehybrid
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