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Strong proficiency with cloud services (e.g.: OpenShift, Azure, AWS), modern JS frameworks (e.g.: React, Angular, NodeJS), SQL and NoSQL DBMS (e.g.: SQL Server, Postgresql, Mysql, Redis, MongoDB), Object-oriented development (e.g.: Java, Node.js, Go, Rust or.
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You will have indepth knowledge and experience in; cloud data lake house; Databricks (preferred) or Snowflake; cloud-native solutions knowledge; SQL or Python; modern DevOps approach; have written data code AND also the CI/CD pipelines.
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At least 1 year experience with cloud computing (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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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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Supermicro is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide.
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Run the Analytics team as a modern software engineering team with a focus on speed to market and tangible business value generation. Modern Data Stack experience (Snowflake, Synpase, Databricks, Redshift, DBT, and/or Airflow.
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Experience with AWS cloud services : EC2 , EMR, RDS, Redshift , Modern data platforms, Snowflake , dbt , Fivetran and Airflow. 3+ years of experience with Cloud based DW such as Redshift , Snowflake etc.
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Frequency of travel is about twice a month, on average - This includes occasional travel for internal events (sales kickoff, technical summit), as well as for cloud security and DevSecOps industry conferences As a Palo Alto Networks Solutions Architect (SA), you will aim to build influential relationships with key technical decision makers at customers.
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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.
$190,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges. required with AWS/Cloud development/computing and OpenCV experience.
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Experience with cloud DevOps tooling and expertise in container native systems and associated security and scaling considerations – ability to work with and build tooling that works in a multi/hybrid cloud environment with modern CI/CD, IaC, DataOps, and DevSecOps best practices.
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Demonstrated experience with hand-on Infrastructure as Code (IaC) development and deployment in Hybrid Cloud (AWS, Azure and GCP) deployments, network architecture, engineering or development experience in network automation frameworks, public cloud infrastructure as code frameworks and solutions for service provider or large enterprise networks.
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Experience with cloud computing platforms, such as AWS, Azure, or GCP.Experience with DevOps and Agile development practices including Kanban. Summary:The Data Protection Platform Engineering Manager will play a crucial role in our organization, overseeing storage platforms and solutions used for backups, operational recovery, disaster recovery and leading a team of talented engineers.
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This technology will revolutionize High-Performance (HPC) and Cloud computing, as well as other industries where low power interconnects are critical like camera sensors, autonomous vehicles, and aerospace.
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This role will be part of a dedicated hybrid actuarial/data science team designing and delivering powerful analytical tools utilizing statistical modeling, machine learning, cloud computing, and big data platforms to enhance or overhaul core actuarial processes For Commercial Lines this team is responsible for all modeling that pertains to pricing, class plans, and profitability.
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