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3+ years of experience with Big Data tools/technologies like Hadoop, Spark, Spark SQL, Kafka,Sqoop, Hive, S3, HDFS, or. The client Corporation is currently seeking an experienced Big Data Engineer Thesuccessful candidate must have Big Data engineering experience and must demonstrate an affinity forworking with others to create successful solutions.
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Proficient in Python/R, PyTorch/TensorFlow, SQL, Big Data and cloud technologies. PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics a big plus.
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Knowledge of some of the main components of Azure Analytics: Azure Data Processing Technologies (DataFactory, Databricks), Azure Big Data Technologies, Databricks, Synapse. The ideal candidate will have extensive Microsoft/Azure data services and Databricks technology experience.
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2+ years experience on Big data pipelines/DAG tools like Airflow, dbt is required. This role will primarily be responsible for building out our analytics platform on Databricks, using dbt and Python for data transformations.
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Experience working with GCP or AWS big data and ML services like VertexAI, BigQuery, Apache Beam, and PubSub. As a Staff Software Engineer working on our Data Infrastructure you will report to the Head of Production Engineering and Cloud Operations, and you will help us design and implement our big data and machine learning capabilities on Google Cloud.
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Commercial grade database management system, data warehouses and/or big data such as SAP HANA, Oracle, MS SQL, Hadoop, or cloud computing platforms (Azure, Google, AWS, etc.
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This role is cloud facing and requires hands on experience in building and managing data engineering code in modern cloud-based technologies such as Google Big Query or equivalent. Prior experience with health information systems and/or patient financial service systems preferred Strong SQL and relational database design/development skills Development experience with cloud-based modern data warehouses such as Google Big Query or equivalent.
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Build high-performing data processing frameworks leveraging Google Cloud Platform and utilizing GCP Services like Big Query, Python, Composer, Dataflow, GKE, Pub-Sub, Cloud Monitoring. As a member of the Data and Analytics organization, you will be responsible for designing, building, and maintaining best-in-class data engineering pipelines aimed at driving best-in-class solutions primarily using Cloud platforms like GCP. You will collaborate with cross-functional teams, including data scientists, analysts, business SME's and software engineers, to ensure the efficient and reliable processing, storage, and retrieval of data.
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Implementing BIG-DATA platform for HIE interfaces using Mongo DB, Apache Spark, HDFS, Zookeeper, and Ambari. Converting the HL7 messages into necessary format and storing data in the MYSQL and SQL databases per architecture and making it easy for FHIR interface.
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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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Work with big data technologies like Azure Databricks, Apache Spark & Palantir. Five (5) plus years of experience in data engineering, machine learning, and cloud tech developing production grade software components and solutions.
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Strong knowledge in Machine learning and AI.Strong experience in Azure Big Data Technologies like Azure Data Lake, ADLA, HDInsights, Databricks, EsgynDB etc. Experience implementing and automating models created by data science teams (i.e. Spark, Scala, Hive, Python, R, etc.
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Experience with multiple large-scale Enterprise Hadoop or Big Data, Data Bricks, Cloudera, HD Insights, or other environments focused on operations, design, capacity planning, cluster setup, security, performance tuning, and monitoring.
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Familiarity with Big Data technologies like Snowflake, Apache Beam/Spark/Flink, and Databricks. Embark on a leadership role within the Blue Yonder Data Science and Machine Learning team as a Staff Data Scientist, steering our machine learning platform that processes real-time data and powers deep learning models, generating billions of predictions daily.
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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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big data jobs Title: hadoop consultant Company: Joveo Us in Dallas, TX
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