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Job Req ID: 24386 About Supermicro: 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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Comprehensive expertise in a wide array of systems and technologies, Department of Defense (DoD) or equivalent Command, Control, Communication, and Computers (C4) systems, data science, big data analytics, ML, AI, and cognitive science is ideal.
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics. Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. Professional certifications in cloud computing (e.g., AWS Certified Solutions Architect, Microsoft Certified Azure Solutions Architect, Azure Data Engineer, SnowPro Core) and/or big data technologies.
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Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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Utilize Databricks for big data processing, analytics, and machine learning workflows. If you are passionate about data engineering, have a strong background in AWS and Databricks, and thrive in a collaborative and innovative environment, we want to hear from you.
$146,400 - $175,100 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Have experience with both proprietary and open-source big data technologies and platforms (Snowflake, Vertica, Hive, Spark, Presto, Airflow). The individual will work in the capacity of a Senior Data Engineer focusing on the data deliverables for Business and Studio.
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Delivery experience in Data Engineering with Google Cloud Platform including Big Query, Dataflow, Cloud Data Fusion, Cloud Composer, Dataproc, Cloud Pubsub, Cloud Function etc. Senior Data Scientist.
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Experience with data warehouse and big data technologies such as Azure Synapse Analytics, Azure Data Lake Storage, Spark, Kafka, Databricks, and Containers. Support migrating big data workloads like Hadoop to Azure services like HDInsight.
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Automate data platform deployment and configuration using Terraform, ARM templates and Azure DevOps. Automate data platform deployment and configuration using Terraform, ARM templates, and Azure DevOps.
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As a Sr. Big Data Engineer, you will work with a variety of talented teammates and be a driving force in technical initiatives that will accelerate analytics at Client. Big Data Engineer.
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Architect data analytics solutions on Azure using services like Synapse Analytics, Databricks and Machine Learning etc. Experience with ETL tools such as Azure Data Factory and Databricks.
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Implement metadata management, data lineage, and auditing capabilities on Azure data platforms using Purview. Migrate on-premises databases and data warehouses to Azure services such as SQL Database, SQL Data Warehouse, etc.
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10+ years of experience in cloud data architecture with a focus on Microsoft Azure. To provide Architecture Solution to Design and implement cloud data solutions on the Microsoft Azure platform.
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big data jobs Title: senior developer Company: Cognizant
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