351 to 375 of 1,367 Permanent Google-Cloud-Platform Jobs

frameworks (Django, Flask, FastAPI). Experience with REST APIs, microservices, and backend development. Knowledge of databases (PostgreSQL, MySQL, MongoDB). Familiarity with cloud platforms (AWS/Azure/GCP) and CI/CD practices. Strong problem-solving, debugging, and communication skills. More ❯

Excellent communication skills for conveying technical vision to stakeholders - Hands-on knowledge of data services like Azure Data Lake, Fabric - Experience with other cloud platforms such as AWS, GCP - Knowledge of Generative AI, LLMs, Azure AI Foundry - Experience refactoring applications for Azure cloud-native technologies - Ability to produce architectural documentation - Awareness of security, compliance, governance in cloud More ❯

of security and compliance. Qualifications Active Secret or Top-Secret Clearance eligibility. 4+ years of experience implementing enterprise-grade infrastructure solutions. Demonstrated expertise with cloud platforms (Azure, AWS, GCP) and multi-cloud strategies. Proficiency with infrastructure-as-code tools including Terraform, Ansible, and Crossplane.io. Experience building and optimizing GitLab-CI pipelines for infrastructure automation. Deep knowledge of Kubernetes More ❯

. Hands-on experience with HSMs (e.g., Thales, SafeNet) and PKI platforms (e.g., Entrust, eMudhra). Experience with cloud-native KMS solutions (e.g., AWS KMS, Azure Key Vault, GCP Cloud KMS). Familiarity with scripting and automation (e.g., Python, PowerShell, Terraform). Excellent leadership, communication, and problem-solving skills. What we will do for you: Competitive compensation Pension More ❯

non-functional requirements, along with developing high-level execution plans to guide development teams through implementation. Skilled in designing application landscapes for cloud environments (Azure preferred, AWS/GCP beneficial). Expertise in modern integration patterns, including REST/SOAP-based APIs, message-driven and event-driven architectures, and legacy integration methods such as batch processing and file-based More ❯

and environment governance. Ability to lead cross-functional teams, manage competing priorities, and influence stakeholders at all levels. Hands-on experience with cloud platforms (AWS/Azure/GCP), containerisation, or virtualised infrastructure is highly desirable. Typically a Bachelor's degree; or a Master's degree; or a PhD; or equivalent experience. In-depth expertise in key engineering principles More ❯

You'll ideally have commercial experience with most of the following; ** Modern .Net (C#, MVC, .Net Core, Web API) ** Databases (ideally SQL Server) ** Cloud Services (Azure, AWS or GCP) ** HTML, CSS and JavaScript (ideally Angular or Reactjs). The following is highly desirable; ** Microservices ** Elastic Search or Apache Kafka ** Experience or interest with AI Salary for this role ranges More ❯

You'll ideally have commercial experience with most of the following; ** Modern .Net (C#, MVC, .Net Core, Web API) ** Databases (ideally SQL Server) ** Cloud Services (Azure, AWS or GCP) ** HTML, CSS and JavaScript (ideally Angular or Reactjs). The following is highly desirable; ** Microservices ** Elastic Search or Apache Kafka ** Experience or interest with AI Salary for this role ranges More ❯

using tools such as Plotly, Dash, Matplotlib or Streamlit cloud and tooling : experience with AWS (S3, Lambda, Bedrock, Athena, or SNS), or other cloud services Azure, or GCP; and familiarity with version control (Git/GitHub), command line, and IDEs software engineering practices : unit testing (e.g. pytest), code reviews, and general good practice in collaborative development applied data More ❯

using tools such as Plotly, Dash, Matplotlib or Streamlit cloud and tooling : experience with AWS (S3, Lambda, Bedrock, Athena, or SNS), or other cloud services Azure, or GCP; and familiarity with version control (Git/GitHub), command line, and IDEs software engineering practices : unit testing (e.g. pytest), code reviews, and general good practice in collaborative development applied data More ❯

using tools such as Plotly, Dash, Matplotlib or Streamlit cloud and tooling : experience with AWS (S3, Lambda, Bedrock, Athena, or SNS), or other cloud services Azure, or GCP; and familiarity with version control (Git/GitHub), command line, and IDEs software engineering practices : unit testing (e.g. pytest), code reviews, and general good practice in collaborative development applied data More ❯

Streams)? Select Which statement best describes your hands on responsibility for architecting and tuning cloud native data lake/warehouse solutions (e.g., AWS S3 + Glue/Redshift, GCP BigQuery, Azure Synapse)? Select What best reflects your experience building ETL/ELT workflows with Apache Airflow (or similar) and integrating them into containerised CI/CD pipelines (Docker, GitHub More ❯

systems in production, so you should expect to apply XP techniques like TDD and SOLID and be comfortable with practices like IaC, CI/CD and Observability. Skills: Python GCP, AWS Kubernetes, Docker, ECS FastAPI, Django PostgreSQL, MongoDB Serverless, Container-based and Event Driven Architectures The money is good too – up to £100k plus benefits including nonus, share options and More ❯

systems in production, so you should expect to apply XP techniques like TDD and SOLID and be comfortable with practices like IaC, CI/CD and Observability. Skills: Python GCP, AWS Kubernetes, Docker, ECS FastAPI, Django PostgreSQL, MongoDB Serverless, Container-based and Event Driven Architectures The money is good too – up to £100k plus benefits including nonus, share options and More ❯

Requirements: Strong backend expertise with Java, Spring Boot, Microservices, Hibernate, and SQL. Proven experience with BPM processes and workflow integration. Knowledge of cloud platforms (AWS/Azure/GCP), CI/CD pipelines, DevOps practices, and API design. Applicants must be eligible to work full-time in Ireland without restriction. Excited about this opportunity? Apply now through the link More ❯

proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast More ❯

proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast More ❯

proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast More ❯

proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast More ❯

proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast More ❯

findings in simple terms Nice to Have: Experience with SQL or databases Exposure to data visualisation tools (e.g., Tableau, Power BI, matplotlib, seaborn) Understanding of cloud platforms (AWS, GCP, or Azure) Previous internship or project work in data science or analytics If you’re excited to grow your career in data science and make a real impact with your More ❯

findings in simple terms Nice to Have: Experience with SQL or databases Exposure to data visualisation tools (e.g., Tableau, Power BI, matplotlib, seaborn) Understanding of cloud platforms (AWS, GCP, or Azure) Previous internship or project work in data science or analytics If you’re excited to grow your career in data science and make a real impact with your More ❯

findings in simple terms Nice to Have: Experience with SQL or databases Exposure to data visualisation tools (e.g., Tableau, Power BI, matplotlib, seaborn) Understanding of cloud platforms (AWS, GCP, or Azure) Previous internship or project work in data science or analytics If you’re excited to grow your career in data science and make a real impact with your More ❯

findings in simple terms Nice to Have: Experience with SQL or databases Exposure to data visualisation tools (e.g., Tableau, Power BI, matplotlib, seaborn) Understanding of cloud platforms (AWS, GCP, or Azure) Previous internship or project work in data science or analytics If you’re excited to grow your career in data science and make a real impact with your More ❯

models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version control systems (e.g., Git) and CI/CD practices for ML workflows. Experience 3+ years of hands-on experience as a More ❯