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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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Big Data Analytical Platforms: Experience with big data technologies like Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc. Strong understanding of big data technologies such as Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc.
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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings.
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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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Be a thought leader and subject matter expert on enterprise data platforms (Big Data, AWS, Snowflake, EDW, ODS, Mosaic). Demonstrated experience with data platforms: ODS, EDW, Big Data and Cloud.
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Work with big data technologies like Azure Databricks, Apache Spark & Palantir. 8+ years of experience in data engineering, machine learning, and cloud tech developing production grade software components and solutions.
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2-4 years of experience in modern data technology stacks such as Google Big Query, Snowflake, Databricks, etc. Handle a variety of data sources such as Salesforce CRM, Pardot, Marketo, BigQuery, Google Analytics 360, Segment, Mixpanel, InfoMatch, Treasure Data CDP, among others.
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Experience working with big data distributed programming languages, and ecosystems: Spark, Hadoop, MapReduce, Pig, Kafka. Experience with common data science tools such as Python, R, Pytorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms (Azure AutoML, SageMaker, DataBricks, DataRobot and H2O.ai.
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The initiatives will include both short-term and long-term research in areas such as artificial intelligence, machine learning & data mining, natural language processing, big data systems, information and data visualization, and social & cognitive science.
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The primary mission of the Vendor Master Data Analyst is ensuring the integrity of Vendor Master Data in SAP (Stewardship) and other Master Data Management reporting and analytics tools.
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Azure, ADF, Databricks, Data Factory, ADLS KeyVault, Terraform, Azure DevOps, DBT. Lead the design, development, and implementation of data pipelines and analytics solutions using Azure data services, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure SQL Database.
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Solid experience implementing data lineage, data quality and data observability for big data workflows. Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka.
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Demonstrated ability to work with cloud computing and data storage tools, preferably AWS S3, Redshift, GCP, Big Query, Snowflake, Google analytics. The ideal candidate will have a thorough understanding of big data and data warehousing, and prior knowledge/use of SQL to develop and automate reporting.
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The role sits within the Group Claims function and reports to the Group Claims Data and Insights Manager, the data scientist will be part of a global agile scrum delivery team and will be expected to work with the team to meet the sprint goals, which drive towards the data platform product vision.
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big data jobs Title: hadoop consultant in Atlanta, GA
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