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You will have a technical and business understanding and thought leadership on approaches to industry leading deployments of Data Lakes, Data Warehouses, Data Marts, and the progression of data from raw/bronze to curated/gold environments with an interest in all tools/technologies including Python, Matillion, Snowflake, Databricks and Azure.
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At least 2 years of experience in Cyber Operations, Data Loss Prevention (DLP), Security Operations Center, or Insider Threat. You have superior knowledge of Data Loss Prevention (DLP), data analytics, incident management, or investigative programs and the ability to identify risks and advise on solutions and mitigations.
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If you're interested in a long-term career at Capital One, the Data Science internship could be a great way to begin your career journey! Experience or academic work with large scale data analysis Data Science Internship.
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Circuit Court Clerk's Office (1): We will hire one student who may be assigned clerical work to include filing, shredding, data entry and other projects. Public Utilities (up to 6): We will hire students depending on the student's studies and interest they could be assigned to work on current projects at Civil, Mechanical, Environmental, engineering-related duties; working with mechanical equipment and instrumentation, data collection, quality assurance as well as working on special projects at either our Water Reclamation Facility or Solid Waste Division.
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10+ years of experience in Master Data Management project implementation/development, Informatica MDM trust settings & validations for both real time and batch solutions projects. Experience in Informatica MDM publishing, JMS, Informatica MDM Architecture and Data Flow.
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Experience in Informatica MDM match/merge, debugging Informatica MDM-related configuration, data issues. End to End implementation of Master Data Management for ERP systems. Partner with leads of all the MDM domains to produce efficient master data solutions.
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Understanding of key aspects of Data and Analytics such as Data Engineering, Analytics and Visualization, DataOps, Master Data Management, and Data Governance. Must have experience moving data workloads to one or more cloud platforms (AWS, Azure, GCP) and delivering data services via Agile methodology.
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Hands-on experience in SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL,Azure SQL Database, Azure SQL Datawarehous e Hands-on experience in deploying and maintaining large-scale data processingpipelines.
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Works with the Trauma Registrar(s) to assure that data entry into the Trauma Registry is accurate, validated and up to date. These activities include managing data entry into the trauma registry, developing reports based on queries from the database, assuring timely mandated submission of state, national, and organization trauma data.
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ITIL, ServiceNow); Designing and developing large-scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker, Cloud IAM, etc.
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The MEP Project Manager, Data Center Construction is primarily responsible for leading and managing the design, preconstruction and construction activities on a given project(s). Experience with delivery of mission critical data center facilities.
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Experience in writing queries (SQL, Python, R, Scala) as needed and experience with various data technologies such as Azure Synapse or SQL Server, Snowflake, Databricks. Enterprise data modeler provides expert support across the enterprise information framework, analyze and translate business needs into long-term solution data models by evaluating existing systems and working with a business and data architect to create conceptual data models , data flows.
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Support Asset Management projects performing data analytics, operational and organizational assessments, condition assessments and overall performance evaluations of water/wastewater/storm water facilities.
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Presto, Hive, SparkSQL, Cassandra, or Solr other Big Data query and transformation experience a plus. Expertise in Cloud Data Warehouses in Redshift, BigQuery or analogous architectures a plus.
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Knowledge in at least four of: GitHub, DataBricks, FastAPI, Algorithms/Algorithm design, NLP, Machine Learning, Data Mining, Docker, Linux, Process Engineering, HuggingFace, Kubernetes, AzureDevOps.
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data job in Richmond, VA
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