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The candidate will be expected to be familiar with system reliability engineering tools, such as reliability block diagram, statistical modeling and data analytics. - Ph. D. in Reliability Engineering, Physics, Electrical, Mechanical or Materials Engineering or a related field.
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Lead development of concepts of operations, requirements definition, analysis and engineering, system architecture, system analysis and design, interfaces, data architectures, verification and validation, system integration, system and operational performance analysis, and life cycle cost and estimation procedures.
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Experience with data engineering and big data technologies such as Apache Airflow, Trino, and AWS EMR. Experience using Infrastructure as Code (IaC) best practices for provisioning and configuring cloud services including experience tools such as Terraform or AWS CDK.
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Whether you’re telling a data story in ways our clients never imagined or building advanced AI models with automated data engineering, the core purpose will be centered on using data to impact people in a meaningful way.
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Our engineering, cloud, data, experience design, and talent solution capabilities accelerate transformation and impact for enterprise clients. Experience the power of transforming digital engineering for Fortune 500 clients.
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Experience with notebook environments and big data engineering tools such as: Databricks, Sage Maker, Google Colab, Jupyter, etc. Lead Data Engineer, Big Data Engineering.
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Coordinate site change/configuration management process development with site System Engineering and Integration team to manage data collection and data input within the DCIM portal.
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Data Engineering: data schema, databases either relational or otherwise, data preparation, and the variety of data storage options. This is ideally across a broad range - Infrastructure, Data, Security, Compliance, and more.
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Strong in data structure, ETL, data warehouse, and related data engineering technologies. 6+ years of experience in software engineering, and 2+ years in data engineering.
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At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure.
$233,100 a yearExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Extensive experience in the areas of electrical and radio frequency engineering; application design, refinement or adaptation for military application; and full cycle project support from conception to completion.
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Master's Degree in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in "STEM" field (Science, Technology, Engineering, or Mathematics.
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Bachelor's degree in math, engineering, physical science, operations research, data science, or a related field. Operations and Systems Analysts apply Model-Based System Engineering (MBSE) principles and tools to identify and analyze trends in big data to solve real-world problems.
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Data Engineering & Backend Proficiency: 7+ years of experience as a Big Data Engineer or Backend Engineer, demonstrating a strong understanding of data systems design and development.
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Bachelors degree in Computer Science, Information Systems, Mathematics, Operations Research, Statistics, Engineering, or related field from an accredited college or university, and 8+ years of relevant experience.
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data engineering jobs in Washington, DC
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