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Exp designing and delivering data engineering solutions with Databricks Exp in Azure Databricks Experience in Data Engineer in zure Big Data Environment Expertise in ETL tools i.e. (Infomatica, Talend, SSIS, Data Stage) Expertise in Implementing Data Warehousing Solutions Exp with working in Agile (KANBAN, Scrumban) environment Exp in zure stack ( zure Data Lake, zure Data Factory) Exp in Scala or Python, T-SQL.
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We are seeking a skilled Machine Learning Engineer with expertise in Azure, Databricks, and MLflow, as well as strong full-stack capabilities, including experience with React.
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OpenShift, Anthos, Google Kubernetes Engine (GKE), Azure Kubernetes Services (AKS), Amazon Elastic Kubernetes Service (EKS), Hashicorp Nomad. Secret Management tools such as Hashicorp Vault, CyberArk, Azure Key Vault, Google Cloud Secret Manager or equivalent.
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Microsoft: Azure Administrator, Azure DevOps Engineer, Azure Architect, MCSE. Experience with administration, automation, and orchestration of large-scale Windows and Linux environments using configuration management solutions, Knowledge in administering and managing infrastructure as code (git, Azure DevOps (VSTS), Azure CLI, ARM, Terraform, PowerShell.
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Azure Logic Apps. - Azure Event Hub. Knowledge with cloud (Azure preferred) - Azure Integration services. - Azure API Management. - Azure Service Bus. - Azure Functions.
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ETL tools Teradata, MS SQL Server, Data Transformation Services (DTS) Export/Import, SQL Server Integration Service (SSIS), ADF, DataStage, Azure Synapse. Reporting tools SQL Server Reporting Services (SSRS), Power BI Additional Databases: Azure SQL Database, SQL Server Analysis Service (SSAS), EDW, EDL DevOps, Azure Blob, Azure Data Lake, Synapse, AWS, S3, GCP, Azure Functions.
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Experience implementing and maintaining data platform core services (data lake, data integration, data warehouse) and configuring and integrating infrastructure and PAAS (e.g., Azure Data factory, Informatica cloud services, Databricks, Data gateway and Qlik Sense, Power BI.
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DevOps Engineer (Senior) with skills DevOps Engineering, GIT / GITHUB, Jenkins, AWS - EKS, Azure - AKS, Azure - ARM, AWS - CloudFormation, AWS-Apps, GCP-Apps, Azure-Apps, AWS-Infra, Azure-Infra, Azure DevOps (ADO), AWS DBA for location Poland.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Relevant platforms include but are not limited to Amazon Web Services (AWS), Microsoft Azure, Google Cloud, Apigee, Simon, Oracle Cloud, Salesforce, Red Hat and Oracle Enterprise Linux (OEL) Applications and Servers, WebLogic / WebSphere Application Server / Java containers, Oracle Database, Microsoft Windows Applications and Servers, Cache servers, Search engines (Endeca or equivalent), and Repository (SVN / GIT.
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Cloud Infrastructure: Virtual Machines, Azure Database, and storage technologies (Storage Accounts, SQL Server, CosmosDB), Virtual Networks, Azure Site Recovery, Traffic Manager, Azure Automation, ARM Templates, Azure Load balancer, API Gateway and Azure AD.
RemoteExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Proven experience as a data engineer, database architect, or similar role, with a focus on designing and implementing data solutions on the Azure cloud platform. Relevant Microsoft Azure certifications, such as Azure Data Engineer Associate or Azure Solutions Architect, are highly desirable.
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4+ years using cloud-based warehouse/data lake (Preferably in Azure Databricks metastores/catalogs or similar stacks such as AWS Athena/Redshift, GCP Bigquery, Azure ADLS, etc) 4+ years using a cloud-based computing/analytics platform (Preferably in Azure Databricks or similar stacks such as Azure DataFactory, AWS Lambda/Glue, GCP DataFlow, Databricks, etc.
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We are a team of forward-looking professionals in need of a strong candidate with these key required skills :Strong experience building solutions using low code technologies such as PowerApps, Power BI, Power Pages, Power Automate, and Power Virtual Agents, SharePoint online, Dynamics 365 CRM, Azure, SQL, and Dataverse.
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Familiarity with cloud data storage solutions such as AWS S3, Google Cloud Storage, Azure Blob Storage, AWS Redshift, Google BigQuery, Azure SQL Data Warehouse, or others. Proficiency in cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure, and experience with cloud services such as S3, GCS, Azure Blob Storage, and others.
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Strong understanding of features and capabilities of the Microsoft Cloud Platform (Azure, Front Door, Security, Firewalls, Certifications, RedisCache, Key Vault, Service Bus, ASR, Networking, OMS, Blob Storage, Resource Groups, NSG, Application Insights, SQL Server, Sql DB, Load-Balancers, AKS, Azure Monitor, Azure Log Analytics.
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azure job Title: machine learning engineer Company: Advantis Global
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