1,801 to 1,825 of 7,446 Microsoft-Azure Jobs in England

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques ...

Senior Data Engineer to lead on projects, drive engineering excellence, and help shape innovative data solutions across cloud platforms like AWS, Azure, and GCP. Join a high performing team that partners with enterprise clients across sectors to deliver cutting edge data projects. This is a hybrid role … alignment between business goals and technical delivery. What You’ll Bring 5+ years in data engineering with proven delivery in cloud platforms (AWS, Azure, or GCP). Expertise in Snowflake development and optimisation. Strong skills in Python and SQL for ELT/ETL and transformation workflows. Experience with ...

Senior Data Engineer to lead on projects, drive engineering excellence, and help shape innovative data solutions across cloud platforms like AWS, Azure, and GCP. Join a high performing team that partners with enterprise clients across sectors to deliver cutting edge data projects. This is a hybrid role … alignment between business goals and technical delivery. What You’ll Bring 5+ years in data engineering with proven delivery in cloud platforms (AWS, Azure, or GCP). Expertise in Snowflake development and optimisation. Strong skills in Python and SQL for ELT/ETL and transformation workflows. Experience with ...