Top Python Jobs in Dublin

The AWS DevOps Engineer will design and maintain AWS cloud networking architectures, manage hybrid cloud connectivity, and support sales engineering related to customer connectivity solutions. Responsibilities include using IaC tools, enhancing CI/CD pipelines, and collaborating with sales teams for solution design.

Responsible for ensuring quality through testing and automation in web and mobile platforms, involving all stages from development to launch.

The Head of Automation will lead the company's automation transformation, creating AI-powered solutions and building specialized teams across departments to drive operational excellence and business value.

The Senior Data Engineer will design scalable systems, automate ML operations, optimize performance, and enhance infrastructure for data processing and monitoring.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

The Analytics Engineer will design and maintain data models, collaborate with stakeholders for KPIs, ensure data quality, and create visualizations. They will optimize dbt models, write SQL queries, and improve data processes.

Canonical is hiring a Software Engineer to develop features for Kubernetes, focusing on operators and integrations while collaborating in a distributed team.

Lead and manage a team of engineers focusing on optimizing Ubuntu for public cloud performance. Ensure quality delivery and foster growth among team members.

As a Senior Software Engineer, you will develop and manage a MongoDB solution on various platforms, ensuring reliability and security while contributing to a small team focused on impactful projects.

The Automation Test Engineer will design and develop AI-driven automated testing frameworks, mentor junior engineers, and ensure software quality through test automation and machine learning techniques.

The Staff Machine Learning Scientist will lead ML projects, mentor engineers, define new features, conduct research, and collaborate with product teams to deliver impactful ML products.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.