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Kafka, HDFS, Hive, Cloud computing, machine learning, LLMs, NLP & Web development experience is a plus. 10+ years experience in data engineering with data warehouse technologies.
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Strong Experience with cloud-based data warehouses – e.g., Snowflake, Big Query, Synapse, RedShift, etc. Experience with at least one of the following cloud platforms: Microsoft Azure (Preferred), Amazon Web Services (AWS), or Google Cloud Platform (GCP.
$83,000 - $138,200 a yearFull-timeRemoteExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Data engineer responsible for designing, developing the transformation and modernization of big data solutions on GCP cloud integrating native GCP services and 3rd party data technologies also build new data products in GCP. We are looking for candidates who have a broad set of technology skills across these areas and who can demonstrate an ability to design and develop right solutions with appropriate combination of GCP and 3rd party technologies for deploying on GCP cloud.
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Solutions Architect, Azure or AWS Cloud platform, AI/Client & MLOps, Java, Spring, Microservices, Big Data, Streaming, Security, Application tiers & Network tiers. Demonstrated and extensive knowledge of APIs, UIs, infrastructure, network architecture, data architecture, security, new technologies, Cloud migration strategies, and product & vendor evaluation.
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We integrate off the shelf and new development efforts to sustain and enhance the NMEC architecture and by leveraging cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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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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You will be working closely with our Cloud Architect, Solution Architects, Systems Engineers, Software Engineers, and Operations Engineering/Manager as well as Government counterparts to perform and manage our cloud solution, cloud computing strategy and all associated documentation.
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Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Cloud Integration ETL Tools, Cloud Data Warehouse, SQL, DBT, AWS Services Lambda, SNS, SQS, Event Bridge, and IoT core.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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Familiarity with cloud and computing technologies like Hadoop, Apache Spark, AWS, Microsoft Azure, or Google Cloud. Create advanced analytics solutions using cloud technologies while working closely with Tech Product Team and Data Scientists to scale AI/ML Models effectively.
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An experienced Solutions Architect well versed in designing & modernizing big data architectures on Google Cloud Platform (GCP). Responsible for design, development, implementation, operation improvement and debug BI & Big Data Analytics environments on premise or on Google Cloud Management Platform.
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Lead a group of engineers building data pipelines using big data technologies (Spark, Flink, Kafka, Snowflake, AWS Big Data Services, Snowflake, Redshift) on medium to large scale datasets.
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Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark). This position will lead and help to develop a newly formed data-scientist taskforce in delivering impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation.
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Sound experience in Google Cloud Data Services: Big Query, Data Proc, PubSub, Cloud Functions, Cloud Storage, Dataflow, Composer. 7+ years of progressively complex related experience in cloud data engineering and data analysis.
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Technology Analytics - Packages Python - Big Data, Technology Cloud Integration Azure Data Factory (ADF), Technology Data on Cloud-DataStore Snowflake. Experience in large scale cloud data migrations using technologies such as Snowflake, Python, Spark, Databricks.
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big data cloud computing jobs Title: data scientist fraud detection in Phenix-city, Alabama
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