Site Reliability Engineer (SRE)

QuickOps Consulting; Lisboa; Hybrid; EUR 65,000 - 95,000; Full time

Job summary

QuickOps Consulting is seeking a Site Reliability Engineer to strengthen the reliability of our cloud-based data-platform deployments. You will implement end-to-end automation with Terraform, build robust CI/CD pipelines in Azure DevOps, and ensure security controls are embedded in delivery.

You will work across Linux and Windows environments, write automation scripts in Python or Bash, and communicate in English with global teams.

Qualifications

• Advanced end-to-end automation using Infrastructure as Code and CI/CD.
• Terraform expertise for IaC deployment.
• Strong Azure experience (4–5 years) across Storage, Data Factory/Synapse, SQL DB, and cost management.
• Experience with Datadog and Azure Monitor for incident resolution.
• Proficient in Python or Bash scripting.
• Solid Linux (Red Hat) and Windows Server skills.
• Excellent English communication and collaboration.
• Familiarity with security practices and SSL.

Responsibilities

• Provide operational support for data processing and analytics service automations.
• Design, deploy, and maintain cloud infrastructure with Terraform.
• Create and optimize CI/CD pipelines using Azure DevOps and Git.
• Manage Level 2 and Level 3 incident resolutions using monitoring systems.
• Fully automate complex standard requests including cloud accounts and SSL renewals.
• Maintain security controls integrated into delivery and adhere to Agile methods.
• Collaborate with cross-functional teams and stakeholders.

Skills

Cloud automation

English communication

Programming/Scripting (Python/Bash)

Linux (Red Hat)

Windows Server

Security principles

Active Directory knowledge

Tools

Terraform

Azure DevOps

Git

Datadog

Azure Monitor

Azure Data Factory

Databricks

Synapse

Cosmos DB

SSL management

Job description

We are looking for a Site Reliability Engineer!

Project Context:

This position requires a solid technical background and extensive expertise across cloud and automation technologies. The main objective is to accelerate and improve the reliability of infrastructure and data-platform deployments by applying DevOps principles. This is not a basic Level 1 support role: it requires advanced end-to-end automation using Infrastructure as Code and CI/CD, complex problem-solving across Level 1 and Level 2 issues, and the integration of security best practices and Agile methodology.

Goals and deliverables

Accelerate the secure, reliable, and repeatable delivery and operation of cloud infrastructure and data-platform workloads through DevOps practices. Improve cloud adoption and operational efficiency with end-to-end automation, Infrastructure as Code, CI/CD, proactive incident resolution, and security controls built into delivery. This is a hands‑on engineering role that goes beyond basic Level 1 support and requires complex problem‑solving across support levels.

• Provide operational support for data processing and analytics services automations, and continuously evolve them to improve reliability, performance, security, and alignment with business needs.
• Design, deploy, and maintain cloud infrastructure using Terraform.
• Create, manage, and optimize continuous integration and continuous deployment (CI/CD) pipelines using Azure DevOps and Git.
• Manage Level 2 and Level 3 incident resolution using central monitoring systems such as Datadog and Azure Monitor.
• Fully automate complex standard requests, including cloud accounts, service principals, and SSL certificate renewals.
• Terraform: Expert knowledge of Terraform for Infrastructure as Code (IaC) deployment is essential.
• Azure DevOps and Git: Strong expertise in Azure DevOps (Pipelines, Boards, and Repos) and excellent proficiency in Git.
• Azure experience: At least 4 to 5 years of confirmed experience with Azure components, including Storage Accounts, Data Factory or Synapse, SQL Database, Azure Machine Learning, and Azure Cost Management.
• Data processing and analytics services: Understands and supports data ingestion and processing with Azure Data Factory, Databricks, Synapse, Azure Data Explorer, Stream Analytics, Event Hubs, Event Grid, and IoT Hub. Works with data storage and databases including Storage Accounts, Cosmos DB, PostgreSQL Flexible Server, and SQL Server. Familiarity with supporting AI and application services is also relevant, including Azure Machine Learning, Cognitive Services, AI Foundry
• IT fundamentals and security: Good knowledge of standard IT environments, including Active Directory and network protocols (TCP/IP, DNS, and HTTPS), as well as security principles such as SSL and network isolation.
• Automation scripting: Advanced proficiency in at least one programming or scripting language, such as Python or Bash/Shell.
• Operating systems: Solid experience with Linux (Red Hat) and Windows Server.
• Communication and collaboration: Excellent communication skills in English.

Work arrangement

Hybrid (1x per week at the office)