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Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics. Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.
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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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Some exposure to Big Data technologies, Apache Spark, AWS, AWS S3, amazon Glue, cloud -based data architecture is preferred. Experience with any of the Data Governance tool – such as Collibra, Alation, Informatica Axon DG, or Apache Atlas.
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Enterprise Applications, Mobility / Collaboration, Big Data / Business Intelligence, Staffing Services, Cloud Solutions, Quality Assurance, Web Solutions, Digital Transformation, Product Engineering, talent solutions, Technology Solutions, Digital Product Engineering, Digital Enterprise, Snowflake, Oracle NetSuite, Apigee, Digital Integration, Data Management & Analytics, Digital Assurance, Extended Engineering Services , AI/ML, Business Process Automation, and TIBCO.
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Knowledge of real-time data streaming and real-time analytics Knowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory) Strong implementation skills and working knowledge of data structures, algorithms and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive); Must have hands-on experience using Spark.
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Strong technical proficiency to contribute to data engineering task in an AWS and Databricks ecosystem. You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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Conduct in-depth risk assessments for Big Technology companies to identify potential risks in the areas of content and activity moderation, consumer data protection, competition, policies and other mechanisms to counter harm, responsible product/service design, data governance and protection and trust and safety and develop and execute controls testing plans, assessing the adequacy and effectiveness of internal controls in mitigating identified risks.
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Experience in one of the public cloud providers – GCP, Azure, AWS.Experience with relational SQL and NoSQL databases, including Postgres and MongoDB.Experience with workflow management tools: Airflow, AWS data pipeline, Google Cloud Composer, etc.
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Define data mapping and lineage to produce accurate reconciliations across multiple sources. The candidate will also be responsible for data mapping and lineage definition in order to produce accurate reconciliations across multiple sources.
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Candidates will be considered from any specialization within surface processes/geomorphology; those focusing on coastal processes, natural hazards, or the cryosphere, and who use tools such as numerical modeling, remote sensing, and big data science are especially encouraged to apply.
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5 years of experience must include: Data analytics and statistical analysis of financial risk data; Policy and regulatory analysis; Data analytics tools including: R, Excel, and PL/SQL; Anti-Money Laundering (AML) and Know Your Client (KYC) guidelines; Oracle and relational databases; and User Acceptance Testing (UAT) and defect management.
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The ACLU seeks a full-time position of Data Operations Director, Volunteer Management System (VMS) in the National Political Advocacy Department of the ACLU's National office in New York, NY. Collaborate on a comprehensive training program for all relevant departments to ensure effective and efficient use of VMS data, tools, services, and technology.
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Understanding of information management principles and practices (i.e. business intelligence, data warehousing, data architecture, data integration, data quality, data governance, data security, master data and meta data.
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The Asset Management Quant Research Engineering team is looking for a Vice President of Data Engineering who wishes to take on the challenge of building a world-class data operation. Deliver datasets from onboarding through mapping and automated DQ so they can be handed off to the Data Operations team for DQ maintenance and consumed by research teams and production.
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Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies. 2+ years of experience delivering Data Governance and Data Quality Management concepts and practices within the financial services industry.
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big data jobs Title: data specialist Company: World Wide Technology in Jersey City, NJ
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