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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau;Possessing a certification(s) in one of the following is a big plus – GCP/AWS/Azure/ data or ML engineering.
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Knowledge and hands-on experience with front-end development (React JS, Next JS, Tailwind CSS) preferred. Hands-on experience with DevOps tools including Docker, Kubernetes, and AWS services (Redshift, RDS, S3.
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Hands-on experience with containerization and orchestration (Docker, Kubernetes) JIRA sprint management to monitor federated work Azure Certifications (e.g., Microsoft Certified: Azure DevOps Engineer Expert, Azure Solutions Architect) #LI-Remote.
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Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks.
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Working knowledge of different version of Dev tools like Visual Studio, Git, Azure DevOps Server, Google Cloud Platform – 5+ years’ experience. Create and execute SQL Queries, Functions and Stored Procs on SQL Server.
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Microsoft Certified: Azure DevOps Engineer Expert. 3+ years of experience as a Cloud Engineer with a focus on Microsoft Azure. As an Azure Cloud Engineer, you will be responsible for designing, deploying, and managing scalable, secure, and resilient cloud environments using Microsoft Azure.
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Experience in Excel, Stata, Python, R, SQL, SAS, ArcGIS/ArcPy, or Cloud computing (Databricks/Spark, Google Cloud, Azure, AWS); Program, build models, and perform regression analyses using languages such as Excel, Stata, R, Python, SQL, or SAS.
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Database (such as Oracle, MySQL, PostgreSQL, MS SQL Server), NoSQL (such as DynamoDB, HBase, MongoDB, Cassandra, Role: Sr. AWS Bigdata Engineer. Extract best-practice knowledge, reference architectures, and patterns from these engagements for sharing with the worldwide AWS solution architect community.
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Administration and support of middleware systems such as RabbitMQ, SQL Server, and ActiveBatch. DevOps-based development using Docker, Kubernetes, Terraform, Azure DevOps, and Azure platform services and components (incl.
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Familiarity with working with data and databases (SQL, MySQL, PostgreSQL, Amazon Aurora, Redis, Amazon Redshift, Google BigQuery). 5+ years of hands-on experience in administering cloud technologies on AWS, especially with IAM, VPC, Lambda, EKS, EC2, S3, ECS, CloudFront, ALB, API Gateway, RDS, CodeBuild, SSM, Secret Manager, Lambda, API Gateway etc.
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Experience authoring SQL to query, load, transform, and retrieve data from various databases including MS SQL Server, Redshift, and PostgreSQL. Experience with cloud services including Microsoft Azure and Amazon Web Services a plus.
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 7+ years of experience in application development including Python, SQL, Scala, or Java.
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Hands on experience with offensive security tools such as Metasploit, Burp, Cobalt Strike, Covenant, Sliver, etc. Experience querying log sources within large centralized logging platforms, e.g. Splunk, Elastic, Cloudera, SQL.
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Hands-on experience using IaC software tools (CloudFormation, Terraform, Azure Resource Manager, GCP Cloud Deployment Manager, etc.) Experience with AWS, Microsoft Azure or Google Cloud Platform configuration and administration of security features and services (including identity and access management, networking, firewalls, encryption.
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Keep pulse of the latest development trends in cloud (AWS, GCP, Azure, etc), data platforms (Databricks, Snowflake etc), databases (RDBMS, SQL, NoSQL, Oracle, etc.) Exposure in complex data migration to and from disparate data systems/platforms as well as to/from the cloud (AWS, Azure, GCP, etc.
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