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Experience with ETL/ELT tools like ADF, Informatica, Talend, etc., and data warehousing technologies like Azure Synapse, Azure SQL, Amazon Redshift, Snowflake, Google Big Query, etc. Strong experience with big data tools(Databricks, Spark, etc.
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Understand the data tables, data architecture and work closely with data engineering team and business owners to determine the best way to extract and present data (BI reporting, machine learning with front-end user interface, etc.
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To lead our team on a mission to build the next generation of our Web and Desktop experiences, reporting directly to the VP of Engineering. By bringing all conversations together in one place, businesses of all sizes in any industry can instantly unlock the power of Ai to unite people, automate tasks, streamline workflows, collect data-driven insights, and turn conversations into opportunities that drive growth.
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Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place. Expertise in design sensitivity analysis via direct (forward) and adjoint (backward) methods, shape/topology optimization and other design optimization techniques; familiarity with machine learning and data science techniques.
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Hands on experience in Qlik Sense development, dashboarding and data modeling and reporting (ad hoc report generation) techniques. Qlik Sense Software Engineer (Data) Experienced in data integration through extracting, transforming, and loading (ETL) data from various sources.
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The Inside Sales Support Specialist will report directly to the Connected Health VP of Sales Leader and will require direct communication and collaboration to support efforts in growing Connected Health sales revenue and elevating brand recognition.
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Experience with data lakes/repositories, and 3rd party data APIs. Domo preferred. Bachelor's Degree in Data Analysis, Data Engineering, Marketing, Computer Science, Information Technology, Business Administration or a related field preferred.
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3 years of architectural design and implementation experience in a Data Warehousing & Business Analytics environment (e.g., Data Lakes, Data Marts, BI, including development and implementation, data analysis, and report writing.
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As the Data Center Manager, you will be responsible for overseeing data center operations, managing computing infrastructure, and ensuring the effective utilization of recent and future advancements in technology.
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Creates data mining architectures / models / protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets. Master’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
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Experienced in either programming languages such as Python and/or R, big data tools such as Hadoop, or data visualization tools such as Tableau. Provide Business Intelligence (BI) and data visualization support, which includes, but limited to support for the online customer service dashboards and other ad-hoc requests requiring data analysis and visual support.
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Our well-established open platforms, including chemiluminescent analyzers, PCR systems and SBS-based gene sequencers, have revolutionized biomedical studies and applications, delivering real-time, high-quality data from DNA/RNA samples.
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Significant experience and subject matter expert knowledge in mechanical testing, including data collection, processing, and analysis for component testing; methodologies and tools used in test data archival; specification of appropriate diagnostics, data acquisition, and digital signal processing techniques; and mechanical test facility operations, upgrade, and maintenance.
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Work At Home Data Entry Research Panelist Jobs - Part Time, Full Time This work-from-home position is ideal for anyone with a diverse professional background, including administrative assistants, data entry clerks and typists, customer service reps or drivers.
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This turnkey solution, hosted on Oracle Cloud Infrastructure (OCI), is designed for extensibility, allowing customers to enrich the application with their data, models, and analytics. FDI leverages data from Oracle's top-tier SaaS applications, such as Oracle Fusion HCM, transforming and loading it into the Oracle Autonomous Data Warehouse (ADW.
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