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Big Data Technologies: Hadoop, Spark, Athena, materialized views. Data Visualization: Tableau, Looker, Power BI, Quicksight. Highly experienced Full stack Engineer with expertise in cloud engineering, data engineering, and data warehousing, particularly within the AWS and google cloud ecosystem.
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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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Design scalable patterns and architecture to support both batch and real-time data products & platform using big data technologies such as Hadoop, SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies.
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Be part of a group of engineers building data pipelines using big data technologies (Spark, Flink, Kafka, Snowflake, AWS Big Data Services, Snowflake, Redshift) on medium to large scale datasets.
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Solid experience with architecting and implementing metadata management including data catalogues, data lineage, data quality and data observability for big data workflows.
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Familiarity with other cloud platforms such as Microsoft Azure, with a focus on their big data and analytics services. Extensive expertise in architecting and deploying scalable AWS IaaS solutions for big data analytics and machine learning, ensuring they are optimized for performance, security, and cost-efficiency.
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PreferredHands on experience in working on Advanced Excel with Smart view Power BI Python Google Big Query Tableau Looker Google Slides SQL experience and familiarity with relational databases.
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Highly skilled in the data space especially in Big Data technologies (Spark, Impala, Hive, Redshift, Kafka, etc.) Expertise in Data governance, data lineage, data quality, and data cataloging.
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Experience implementing monitoring, quality assurance, data validation processes in a relational and big data environment (metrics-driven reliability and performance) BS or MS degree in a quantitative field such as computer science, physics, math, engineering, or economics.
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We have partnered with our client in their search for a Java Spark Developer in Plano, TXResponsibilities As a Software Engineer - you serve as an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way.
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We are seeking a talented AWS DevOps/MLOps Lead to develop platforms for big data and data science on AWS. As models, apps, and data pipelines are created and operationalized, the bigdata and data science team requires engineers with understanding of cloud native technology to develop, manage, automate, and facilitate the operational capabilities of the big data and data science team.
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But helping our partners gain the advantage is not enough for us – we make it our business to maximize it through our pioneering technology and big data mining capabilities. Typically requires the ability to sit for extended periods of time (66%+ each day), ability to hear the telephone, ability to enter data on a computer and may also require the ability to lift up to 10 pounds.
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Solid experience in the following: Cloud Services such as AWS or Azure; Java and Python; Maven; UNIX; Microservices; GIT; REST web services; Software Development; SQL; Databases; Messaging and Events; Caching; Spark; Big Data storage, processing, and consumption.
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Experience in Big data ecosystem using Hadoop, Spark, Scala using Python packages and libraries for large scale data. Strong knowledge in RESTful APIs, Data structures, Algorithms, Collections, Multi-threading and memory management and concurrency.
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DevOps Tools: Docker, Kubernetes, Jenkins, Terraform, Git, Big query, Firebase. Utilizes Apache Airflow for scheduling and monitoring data workflows to ensure timely data delivery.
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