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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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Delivery of FinOps services, FinOps education & enablement of AWS, Azure, GCP, hybrid, and other public cloud environments. The Cloud Optimization/FinOps Solutions Consultantis responsible forthe development and delivery of AWS public cloud and hybrid optimization and FinOps consulting services to customers of varying sizes across multiple industries.
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Demonstrating strong experience in Oracle RDBMS, PL/SQL, AWS RDS, PostgreSQL, Redshift, Databricks, Python, Shell scripting. Certified AWS Cloud Practitioner is strongly preferred.
$100,000 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Microsoft Azure and AWS cloud native services. Knowledge and experience working with cloud computing - e.g. Azure or AWS or GCP (Required) Manage cloud infrastructure (Azure, AWS, and OVH) and take care of the infrastructure backup and the backup checks.
$90,000 - $100,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep expertise in cloud platforms such as AWS, Azure, or GCP, including services such as EC2, S3, Lambda, and Kubernetes. Champion best practices for infrastructure as code (IaC) using tools such as Terraform, CloudFormation or CDK to provision and manage cloud resources.
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Comfortable working in cloud and high-performance computing environments (e.g. AWS, GCP, Databricks, Apache Spark, Snowflake?) Expertise with core data science languages (such as Python, R, Scala), and proficiency with key database systems (e.g. SQL, NoSQL.
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Demonstrate ability to write new code i.e., well-documented and stored in a version control system (we use GitHub & Bitbucket) Good to have experience with Cloud Platforms such as AWS, Azure, GCP and Snowflake Good to have strong programming/ scripting skills (Python, PowerShell, etc.
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Technology Stack: Full Stack/AWS Django/Python REACT/Snowflake/Power BI. Experience with cloud services (AWS, Microsoft Azure and Snowflake) Extensive experience with Snowflake, SQL, PYTHON (Programming views, stored procedures, and functions) ,Python.
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Google Cloud Platform (GCP) or AWS. Across our engineering teams, we also use Scala, GCP, Spark, Kubernetes, Python, TypeScript, Angular, and anything else that helps us get the job done.
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Experience on data pipelines and workflow management tools like Dagster or Airflow and Cloud-based infrastructure like AWS, Google Cloud, Azure. Our current stack is Python, Dagster, MySQL and Snowflake, but we’re early stage and open to change if it makes sense.
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Hands-on with advanced Bigdata technologies like Hadoop, Spark, Scala, Hive, SQL and NoSQL. Experience with Public cloud technologies such as AWS, Azure is plus Ability to quickly learn and implement new technologies.
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Hands on experience with AWS Cloud, Databricks, Unity Catalog, Python, PySpark, Scala, HIVE, Bigdata/Hadoop, and Shell scripts is required. Good working knowledge of Amazon Web Services (AWS) Cloud Platform which includes services like EC2, S3, ELB, Auto Scaling, EC2 Container Service (ECS.
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Extensive experience with Full Stack – Java , Snowflake, SQL, PYTHON (Programming views, stored procedures, and functions) ,Python. Extensive experience with Full Stack – Java , Snowflake, SQL, PYTHON (Programming views, stored procedures, and functions) ,Python.
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This role involves leveraging cloud-based AI resources that support LLM-based application development, such as Azure AI studio, AWS Sagemaker, OpenAI and Google Vertex AI. Design, develop, and deploy private end-to-end AI chatbots and solutions leveraging GenAI / LLM models and RAG pipelines through cloud AI environments, such as Microsoft Azure AI (Copilot) Studio, OpenAI GPT, AWS SageMaker and other platforms.
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3+ years of experience in configuring and tuning cloud services (AWS, GCP, Azure), with AWS preferred. The group provides a key function within the department that allows us to achieve the velocity and quality needed inside of our DevOps model, delivering large scale data and HPC solutions on the cloud.
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