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Experience working with big data distributed programming languages, and ecosystems such as Spark, Hadoop, MapReduce, Pig, Kafka. Clean, preprocess, and transform raw data into a suitable format for machine learning models.
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Experience working with large datasets and big data technologies, preferably cloud-based, such as Snowflake, Databricks, or similar. Responsibilities:The Data Engineering team is looking to fill a Senior Data Engineer responsible for designing and implementing ETL/ELT data pipelines, designing and implementing database schema/tables/views, and building batch processes leveraging Airflow for several projects.
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Responsibilities: •Architect and design big data storage and analytic solutions on Hadoop–based platform, create custom analytic and data mining algorithms to improve performance.
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The Adobe Experience Platform handles petabytes of data on behalf of organizations allowing them to have a centralized and standardized data platform applying data science and machine learning (ML) to spectacularly improve the design and delivery of rich, personalized experiences.
$154,000 - $278,800 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Big Data Technologies:Distributed Computing: Tools like Apache Spark, Hadoop. Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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4+ years of experience with scientific scripting languages (e.g., Python, R, SAS), as well as big data frameworks such as Hadoop MapReduce. 6+ years of experience of Data Science model development with a combination of Bayesian statistics, regression analysis (beyond linear regression), forecasting/predictive analytics, multivariate testing, supervised learning, unsupervised learning or time-series analysis, implementing large-scale optimization models (mixed integer and linear programming, genetic algorithms) and using optimization packages such as Gurobi, CPlex,or others.
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The successful Software Engineer candidate will be part of the KBR team supporting the Test Resource Management Center’s (TRMC) Big Data (BD) and Knowledge Management (KM) Team working on prototype BD and KM systems for DoD test ranges and various acquisition programs.
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Proficiency in at-least one of the following programming languages - Python, Scala or Java. Experience in multi-threaded, concurrent programming and synchronization Cloud technology experience on platforms like AWS, Microsoft Azure, Google Cloud Experience developing Big Data applications using java, Spark, Kafka is a huge plus.
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Key Qualifications: 3+ years of experience building enterprise level applications on large-scale distributed systems Knowledge of BI concepts and implementation experience on Cloud with databases like SnowFlake, Big Query, Cloudera Understanding of fundamentals of object-oriented design, data structures, algorithm design, and problem solving Programming experience in building high quality software.
$138,900 - $208,300 a yearExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Data Modeling: Requires knowledge of cloud data strategy, data warehouse, data lake, and enterprise big data platforms; Data modeling techniques and tools (For example, Dimensional design and scalability), Entity Relationship diagrams, Erwin, etc; Query languages SQL / NoSQL; Data flows through the different systems; Tools supporting automated data loads; Artificial Intelligent - enabled metadata management tools and techniques.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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Installs processes for auditing target data stores and ensuring data qualityBuild the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Informatica, Python, SQL and AWS ‘big data’ technologies.
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Research in Computational Data Science and Engineering includes: big data and computational statistics, AI and Machine Learning, internet of things, large and complex systems, intelligent transportation and infrastructure systems, remote sensing, autonomous vehicles, virtual and augmented reality, e-commerce, image and video processing, scientific and interactive visualization, high-performance computing, scalable algorithms, bioinformatics, and multi-scale multi-physics engineering systems.
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Knowledge of data testing in DBT and Google Cloud certifications are a big plus. Experience building and optimizing ‘big data’ data pipelines, architectures and data sets in GCP.
$81,500 - $137,500 a yearFull-timeExpandApply NowActive JobUpdated Today
big data jobs Title: machine learning engineer platform
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