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Minimum education and experience required: Master’s degree in Information Systems, Computer Engineering, Computer Science, Mathematics, Statistics or related field of study plus 2 years of experience in the job offered or as Data Visualization Associate, Software Engineer, Data Analyst, Reporting Analyst, or related occupation.
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Master's in Computer Science, Computer Information Systems, or Management Information Systems plus three years of experience in software development using Python, Alteryx, SQL, OTBI reporting, Oracle BI Publisher, Oracle Fast Formulas, HCM Extracts, SOAP, REST API services, Workday HCM Modules, Workday Studio, Enterprise Interface Builder (EIB), Workday Report Writer, AWS Application Integration, Tableau, Excel, and JIRA. Excellent communication (oral and written) skills are also required.
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Highly experienced Full stack Engineer with expertise in cloud engineering, data engineering, and data warehousing, particularly within the AWS and google cloud ecosystem. Big Data Technologies: Hadoop, Spark, Athena, materialized views.
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Director, Software Engineering - Cloud Governance & Site Reliability Engineering (SRE) Capital One is seeking a Director of Software Engineering to lead, manage, mentor, and build extremely talented software engineering teams to deliver game changing technologies in the field of Cloud Governance and Site Reliability Engineering (SRE.
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Hands-on experience with Databricks and Snowflake for data engineering and analytics. Required background/ Skillsets: Prior working experience in Data bricks Snowflake Python Data science background Proficiency in Python for software development and scripting.
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We're helping patients get the best care possible by working on digital health experience, analyzing big data to streamline the delivery of care, and reaching out to medically complex patients to better understand their needs.
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Work with business users, data product owners, platform owners, enterprise architects, data management owners, and data engineering teams to ensure the data supply chain and the enterprise data products are built with high performance, high availability, and maintainability standards using current and emerging big data technologies.
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Our areas of expertise include: Multi Cloud Managed Services woven around SAP Ecosystem, Salesforce, Oracle, SNOW (ServiceNow), DevOps, Data Engineering, Technology Lifecycle Management, AI/ML stack, Web Design/Development, Mobile Application Development, E-commerce, Cloud Expertise (AWS, Azure, GCP) etc.
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As a member of the Data Loss Prevention (DLP) engineering team, you will play a key role on a team of cyber technicians and engineers to create, implement, and maintain DLP Controls using SaaS and IaaS based solutions to reduce risk and enforce Capital One's Information Security Policy and Standards.
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5+ years of experience in a technical security role (e.g. Penetration Testing, Red Team, Application Security, Infrastructure Security); or master’s degree in computer science/engineering or related cyber field, and 2 years of relevant experience.
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Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka. Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka.
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Our specialized experience includes design for data centers, healthcare, science and technology, high-rise buildings, clean energy, education, and other building types as well as structural and building sciences, infrastructure asset management, advanced robotics, and more.
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It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
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Experience in Modeling, Simulation, and Analysis (MS&A) engineering or related technical areas, such as, Data Science, Operations Analysis, Behavior Modeling, Predictive Analysis, Model Based Systems Engineering (MBSE), Industrial Engineering, etc.
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Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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data science engineering big jobs Company: Apple in Plano, TX
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