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Systems engineers, desktop support technicians in IT Operations, and data engineers and product managers working to unify data in our enterprise data platform. This includes enterprise automation (e.g. workflow automation, tools integration), enterprise systems and information technology (IT) operations (e.g. internal systems and network administration, enterprise identity, desktop support), and enterprise data platform (e.g. data warehousing/data lake, enterprise data product development.
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The Senior Enterprise Data Governance Steward partners with counterpart Data Stewards within the Business Process Owner’s (BPOs) line of business, Internal Audit and Enterprise Risk Management (ERM), to ensure consistent adoption, approach and adherence to the treatment of data across the Bank.
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The role elevates data quality across the MVW Enterprise and expand the value of business data to drive growth with a focus on the following areas of work: enterprise data strategy and governance, data platform architecture, data engineering leadership, collaboration and alignment, and innovation and continuous improvement.
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The GPS AI & Data Engineering offering is responsible for developing advanced analytics products and applying data visualization and statistical programming tools to enterprise data in order to advance and enable the key mission outcomes for our clients.
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The Sr. Data Engineer is responsible in understanding and supporting the businesses through the design, development, and execution of Extract, Transform, and Load (ELT/ETL), data integration, and data analytics processes across the enterprise.
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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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Provide solution that is based on Reference Digital Integration Layer (Digital Integration Hub) that ties together the Experience Layer, Microservices, Event-based integration, Data management (data streaming), and the system of record applications and data such as Oracle EBS, Oracle Cloud, other ERPs, and other large enterprise applications across the globe.
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Provide financial management and analytical support to PMS-317 staff and leadership, leveraging a myriad of systems including Navy Enterprise Resource Planning (ERP), Program Budget Information System (PBIS), NAVSEA Enterprise Planning Systems (NEPS), Research, Development, Test and Evaluation Documentation System (RDOCS), Procurement Documentation System (PDOCS), Computer Optimized Batch Reconciliation Application (COBRA), NAVSEA Enterprise Data Warehouse (EDW), Advana and COMPASS.
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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.
$97,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Knowledge of Azure Synapse/Snowflake, Azure Data Lake Storage, Databricks, and enterprise data management platforms. TBI ID Number: 23-12055, Business Intelligence Engineer/BI Engineer/ETL Developer/BI Developer/Data Engineer.
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The ECS organization is responsible for delivering effective security solutions to ensure customer and enterprise data and assets are protected in a constantly evolving cyber-threat landscape.
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Be a thought leader and subject matter expert on enterprise data platforms (Big Data, AWS, Snowflake, EDW, ODS, Mosaic). Deep understanding of the architecture of enterprise-scale data processing systems, distributed systems, and cloud computing platforms.
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On-site and remote troubleshooting and resolving complex technical problems on Supermicro equipment in an enterprise environment. Work experience in large enterprise or certification in Windows and Linux environment is a plus.
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The Data Team Product Manager will act as a product owner and product manager of enterprise data warehouse and analytics. The product manager will work with cross-organizational teams such as executives, product teams, portfolio strategy, customer success, and the back-office as well as customers to produce clear and compelling information that will increase understanding of enterprise data and ultimately improve business performance.
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There are various disciplines involved in Enterprise Data & Analytics, including: data source identification and analysis, data engineering, data visualization & data science/machine learning.
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