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The Cloud Data Engineer role will support our Cloud Data Management and Advanced Analytics platforms. Solid understanding of various Data Management and Data Pipeline tools available in AWS. Working knowledge with primary AWS Services like S3, Lambda, Batch, Glue, Athena, EC2, EBS, CloudWatch, CloudTrail, ECS, ECR, EMR, IAM, SNS etc.
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Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and (GCP, AWS, Azure, Snowflake) ‘big data’ technologies.
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Our experts in public health, performance evaluation, and health operations solve the complex problems faced by civilian and military customers alike by leveraging advanced tools including digital transformation, artificial intelligence, data analytics, cloud enablement, modeling, and simulation, and more.
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We are looking for a builder with a deep track record of success creating and growing Navy and USMC focused solutions businesses that can leverage SMX's national position as a leader in cloud and digital transformation solutions.
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Experience working in GCP based Big Data deployments (Batch/Real-Time) leveraging Terraform, Big Query, Big Table, Google Cloud Storage, PubSub, Data Fusion, Dataflow, Dataproc, Cloud Build, Airflow, Cloud Composer etc.
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DLH delivers improved health and national security readiness solutions for federal programs through science research and development, systems engineering and integration, and digital transformation.
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Solid experience with architecting and implementing metadata management including data catalogues, data lineage, data quality and data observability for big data workflows.
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At least 2 year of experience in data engineering using open-source technology stack along with cloud computing (AWS, Microsoft Azure, Google Cloud) Developing new and enhancing existing data processing (Data Ingest, Data Transformation, Data Store, Data Management, Data Quality) components.
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Newer technologies and risk topics such as AI/ML, quantum computing, cloud computing, digital currency, etc. Experience in IT risk transformation services such as IT risk management, GRC, data analytics, policy and standard management, issues management, or IT regulation and compliance.
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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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Education & Experience: Master’s degree in Data Science or related field (or equivalent) with 7+ years of experience in data science, AI, and digital transformation.
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Presto, Hive, SparkSQL, Cassandra, or Solr other Big Data query and transformation experience a plus. Expertise in Cloud Data Warehouses in Redshift, BigQuery or analogous architectures a plus.
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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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Experience with big data technologies (e.g., Snowflake, Google BigQuery) and cloud computing platforms (e.g., AWS, GCP, Azure). Own the technical strategic vision for data science within connected products.
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SAIC's National Intelligence Community (NIC) business unit provides solutions and services supporting digital modernization programs in areas such as system engineering, cloud computing, cyber security, data science and analytics, artificial intelligence / machine learning, application development, DevSecOps, network operations, and secure communications.
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