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Manage and optimize Apache Spark pools for high-performance data processing tasks. Responsible for end-to-end data integration in the Azure platform, this includes all phases of integration development life cycle, requirements gathering, design, build, test, deploy and maintenance.
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Hadoop Data Engineer is a hybrid role with experiences in database management, clustered compute, operating system integration, cloud concepts, storage solutions, application processing, and advanced monitoring techniques.
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Certifications: Relevant cloud and AI certifications (, AWS Certified Machine Learning, Google Cloud Professional Data Engineer). About the Role : Principal Cloud Security Engineer – AIThe Team: Part of the Cloud Security team, responsible for safeguarding an organization's digital assets, data, and applications hosted in cloud environments.
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Our data engineering team is also responsible for quality curation of data to ensure our products You will be joining a talented, fully remote Data Science, Engineering and Analytics team that handles a wide range of requests including customer data processing, weekly report automation, new product development and complex data integration.
$120 - $150 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Responsible for data engineering functions including, but not limited to data extract, transformation, loading, integration in support of modern cloud computing platforms like Azure and Databricks.
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AI Integration: Contribute to the integration of AI and machine learning algorithms into the platform, providing data-driven insights and predictive analytics. Back-End Development: Build robust, scalable, and high-performance server-side components supporting the trading platform's execution, data processing, and analytics.
Starting at $200,000 - $650,000 a year (bonuses)ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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A Process Integration Engineer will lead the manufacturing and process development of III-V laser products. · Hands-on experience with semiconductor processing and wafer fabrication.
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Strong expertise in Apache Spark, Delta Lake, and other Databricks components for data processing and analytics. Leading team in the definition of best practices & repeatable methodologies in Cloud Data Engineering, including Data Storage, ETL, Data Integration & Migration, Data Warehousing and Data Governance.
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Experienced in big data and NoSQL solutions by developing scalable data processing platforms to drive high-value insights to the organization. Designs, develops, and implements ETL/ELT processes using Azure Data Factory, Synapse pipelines, Databricks Notebooks, Event Hub to build integrations from Saas sources such as Service Now, Workday, Dynamics CRM, and Eloqua.
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Experience with ArcGIS, ENVI, QGIS, GDAL, or Python for geospatial data processing. Recommend data architecture and schematics, ETL process/Tool, data governance, and potential integration with internal and external data, and analytic framework.
$150ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Excellent understanding of Snowflake Internals and integration of Snowflake with other data processing and reporting technologies. Including hands on experience with productionized data ingestion and processing pipelines using Python, Data bricks, Snow SQL.
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7+ years of experience in data engineering, with a focus on data integration, data transformation, and data warehousing. 7+ years Cloud Development (AWS Cloud) for data processing including experience doing ETL processes.
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Including hands on experience with productionized data ingestion and processing pipelines using Python, Data bricks, Snow SQL Excellent understanding of Snowflake Internals and integration of Snowflake with other data processing and reporting technologies Excellent presentation and communication skills, both written and verbal, ability to problem solve and design in an environment with unclear requirements.
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Insights Wrangler: Shape and enhance our data architecture strategy, making high-level decisions on data storage, consumption, integration, and management across cloud platforms (Azure, AWS, or Google Cloud.
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Good knowledge and experience in Azure data integration services such as Azure ADF, Databricks, Synapse. Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure.
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data processing integration jobs Title: engineer in New York, NY
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