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Hands-on Experience in Big Data and cloud technologies tools, i.e. Hadoop, Hive, Iceberg, Kafka, Spark, Presto, Airflow, Elastic Search, Docker and Kubernetes. The Data Science Solutions Engineer at Lucid is setting data science pipeline for our fast growing data team.
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Experience with the Big Data technologies is a plus (Redshift, Hadoop, M/R, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink etc) Design and optimize the big data architecture, including data collection, data governance, data security, data warehouse, data application, algorithm application etc.
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Validate the Duty Drawback data integrity per US Customs compliance requirements and resolve any data discrepancies that resulted from the Drawback data validation, such as HS classifications, unit of measures, quantities, etc.
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Perform metrology tools calibrations and wafer measurements, recording data into corresponding SPC files or database, and performing basic tool maintenance. The Company's components are key elements in large optical network infrastructure builds which enable global networking and largescale computing for businesses and individuals, including data centers and 5G telecommunications networks.
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Knowledge of the modern data stack landscape (Airflow, Dagster, dbt, Atlan, Alteryx, Collibra, Talend, Databricks, Snowflake, Tableau, Metabase, Mode, Superset, Fivetran, Stitch, etc.) You will leverage your intellectual curiosity, analytical mindset, and cross-functional program management skills to define & execute data governance and Master Data Management (MDM) strategies, and foster a culture of data-driven decision-making.
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Building automation monitoring tools for Big Data and working with data engineering-related tools and technologies, including: Kafka, Data Warehouses, and Apache Airflow; - Three (3) years of experience with at least one big data platform (such as Snowflake, Databricks, etc.
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ETL, Big data platform (ADLS / Data Bricks / AI / ML / Synapse / DBT). Prepare and present potential technical designs and solutions for Data pipelines and DataOps in GCP and Azure cloud environments.
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Experience building data pipelines using Hadoop components Sqoop, Hive, Solr, Strong project experience in Big Data, Cloudera Distribution. experience in Big Data, Cloudera Distribution 7.
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Expert understanding of customer identity and customer data in advertising - browser cookies, mobile device identifiers, identity graph, 3rd party identity solutions, privacy compliance, data governance.
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Design, implement, and maintain robust DevOps pipelines for deploying, monitoring, and scaling machine learning development and data engineering. You will apply modern ML Ops, Devops, and data engineering stacks to enable development, training, deployment, and lifecycle management of a variety of ML capabilities; supervised and unsupervised, deep learning and classical.
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Experience using big data technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, pySpark) Experience designing and building highly available, distributed systems of data extraction, ingestion, normalization and processing of large data sets in real time as well as batch, that will be used across engineering teams using orchestration frameworks like Airflow, KubeFlow or other pipeline tools.
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Contribute to driving the eCommerce data strategy and roadmap by offering additional insights and suggestions for improvement while collaborating with external partners and vendors, assisting in project scoping, prioritization, and successful execution.
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The Building/Code Compliance Inspector is further distinguished from the lower level of Building/Code Compliance Trainee in that the latter is the entry-level class, and is in training, learning the full scope of the assigned duties and responsibilities.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Manage and optimize our data analytics infrastructure (Databricks and Snowflake), including monitoring, troubleshooting, and maintaining high availability. Manage and optimize our data analytics infrastructure (Databricks and Snowflake), including monitoring, troubleshooting, and maintaining high availability.
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data entry jobs Title: admin assistant Company: Focusgroupjobs in Fremont, CA
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