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Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, AutoScaling, CloudFormation, LakeFormation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, Cloudtrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.
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Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation: Kafka, StreamSets, Attunity, GoldenGate, Map Reduce, Hadoop, Hive, Hbase, Cassandra, Spark, Flume, Hive, Impala, etc.
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Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalog etc. Minimum of 10 years of experience in big data, database and data warehouse architecture and delivery.
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The VP, Engineering will l ead scaling the global data and software engineering team s in managing the foundational enterprise data platform and creat ing tools and frameworks that enhance data collection and processing, analytics and artificial intelligence , data dissemination , and governance.
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Write Python code in Databricks Notebook for data preprocessing, processing unstructured data/documents, feature extraction, API calls, and application orchestration. Experience developing data engineering and ML pipelines in Databricks.
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CoreWeave builds cloud solutions for compute intensive use cases - VFX and rendering, machine learning and AI, batch processing, and Pixel Streaming - that are up to 35 times faster and 80% less expensive than the large, generalized public clouds.
$190,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Collaborate with Architecture, Infrastructure and Data Science teams to translate their needs or challenges into production-grade Artificial Intelligence and Machine Learning deployment architectures for batch, real-time streaming deployments.
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Our tech stack continues to evolve: Azure Data Factory, Azure Data Lake, Azure Synapse, Power BI, Collibra, Databricks, MLflow, RStudio, Harness CI/CD, OpenShift, GitHub, JIRA. Familiarity with all, and expert in some of the below: Databricks or Spark, MPP databases, ETL, data warehouse design, feature store design, monitoring tools.
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To thrive in this role, you should have ten-plus years of experience in architecture, design, and building a scalable target state architecture for data processing-based on document content including PII/CII handling, policy-based hierarchy rules and Metadata tagging.
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Take part in data cleaning and processing tasks wherever appropriate. Experience with computer vision, signal processing methods, NLP, deep learning methods. Prior experience with data visualization tools and libraries such as Power BI, Tableau, Matplotlib, Seaborn etc.
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We are seeking a highly skilled AWS Data Engineer with expertise in building Data pipelines and processing solutions on the AWS platform, focusing on Databricks, Delta Lake, and Python development.
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The Data Engineer is critical to design, develop, and maintain the infrastructure and systems necessary for the collection, storage, processing, and analysis of large volumes of data.
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Minimum of 1 end-to-end SAP Master Data Governance implementation. Minimum 3 years of experience with/in SAP Master Data Governance. At least 1 year of hands-on experience/expertise in Master Data Governance including (but not limited to): Material Master, Finance Master Data Objects, Customer, Vendor.
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Solid Understanding of Clinical Terminology such as SNOMED, ICD9/10, CPT, HCPCS, READ Solid understanding of healthcare data, particularly electronic health records (EHR) and insurance claims, and experience working with healthcare data standards.
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Experience with managing and optimizing cloud-based data storage and processing solutions. Proficiency in Microsoft Azure cloud services, including Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Data Lake, etc.
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data processing jobs Title: accounts payable Company: Reel Security Of California in Parsippany, NJ
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