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Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, Autoscaling, CloudFormation, Lake Formation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, CloudTrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.
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Familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) and experience in deploying machine learning models in a cloud environment using platforms such as AWS SageMaker and GCP Vertex AI.
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Cloud based tools/solutions including AWS, S3, Databricks, Snowflake, SQL, Python. You will leverage your ability to design, build and deploy data solutions using cloud based compute and warehouse tools that capture, explore, transform, and utilize data to support Artificial Intelligence, Machine Learning and business intelligence/insights.
$105 - $173Full-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 2+ years of experience with AWS, GCP, Azure, or another cloud service. Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Utilize programming languages like Python and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) 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.
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Cloud Architecture Certification (AWS, GCP, or Azure) or strong architecture experience on Cloud. Cloud Lake and Warehouse Snowflake, S3 Data Lake, other comparable technologies.
$118,800 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise with the tools and languages we use to automate cloud infrastructure will also prove valuable in making early contributions to the team, specifically Python, Golang, Cloud (Azure or AWS or GCP.
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Cloud Technologies – Pivotal Cloud Foundry (PCF), AWS, Docker, Apigee gateway. Basic knowledge in SQL, Linux, Windows, Cloud, Sybase, Oracle. Hands on extensive experience in Salesforce platform, particularly in Service, Sales and Financial Cloud.
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Expertise architecting and developing solutions in AWS, Databricks and Snowflake (data engineering) Experience in AWS components including: Lambda, Kinesis/Firehose, Airflow, Glue,Spark, EC2, SageMaker, S3, NoSQL database and API Gateway.
$135,700 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Implement and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions, on a multi-team/product level. 5+ years in large scale big data engineering experience and designing best practices in Programming, SDLC practices, Distributed systems, Data warehousing solutions SQL and NoSQL, ETL tools, CICD, Cloud Technologies (AWS/AZURE),Python/Spark, Datamesh and Datalake, Data Fabric.
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Develops Infrastructure as Code (IaC) using CloudFormation templates and Terraform, YAML files, build specifications, and Python Lambda functions to have a completely automated build and release process for all AWS resource infrastructure and code artifacts.
$126,160 - $189,240 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Build, modernize and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing/quality solutions using AWS, Databricks, Python and other Cloud technology stack.
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Relevant certifications, such as Google Cloud Certified - Network Engineer and optionally certifications related to Azure or AWS. · Hands-on experience with Nexus VPC configurations, Arista MLAG, and Terraform scripting, with an additional advantage if experience extends to Azure or AWS environments.
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Successful candidates will not only demonstrate advanced knowledge of AWS, Databricks, Snowflake, Python, Spark APIs and Event Driven patterns – but have tangible experience with similar efforts to modernize legacy data & analytics platforms from on-premise to cloud.
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