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Fluent in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. Working closely across groups, particularly product, engineering, analytics, and accounting teams to design and manage scalable data life cycles of new and existing products.
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As a data engineer, you have experience spanning traditional DW and ETL architectures and big data ecosystems like Databricks / Snowflake / EMR / Airflow. Dropbox is looking for a Data Engineer to join our Finance Data Engineering (FDE) team to build out next generation Financial data pipelines that power crucial business decisions throughout the organization including metrics (ARR, Churn) that are reported externally to Wall St. The team is responsible for curating Gold Datasets (user, team, product etc) that are the source of truth for analytics and operations at Dropbox.
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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.
Full-timeExpandApply NowActive JobUpdated 24 days ago - UpvoteDownvoteShare Job
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Considerations include variety (structured, unstructured), volume (includes big data), data quality (cleaning and validation of the data) and velocity (batch, stream). Data Science tools like Knime, Dataiku, AWS SageMaker, statistical languages, and packages, e.g., R, Python, Julia, SAS, data visualization tools and techniques, e.g., Tableau, ggplot, matplotlib, R/Shiny, Qlik, data manipulation tools such as SQL, Spark, PySpark and Hive, cloud environments like Azure and AWS, deep learning tools such as Tensorflow, Keras and PyTorch.
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This technology leader will bring in the experience of SaaS/cloud solutions (Azure), data engineering techniques, DevSecOps automation and best practices in building, maintaining, and enhancing state of the art big data Platforms.
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Overall 10+ years of experience as developer in Big data technologies like Databricks/Spark and Hadoop ecosystems. Experience in developing Spark applications using spark-SQL in Databricks for data extraction, transformation and aggregation from multiple file formats for analyzing and transforming the data to uncover insights into the customer usage patterns.
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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, Google Cloud Platform, Azure.
Full-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Any level of experience with Lead design and development of the Big Data Analytics Platform by gathering requirements from the various stakeholders and converting it to technical design and implementation using various Big Data technologies like Apache Spark, Mapreduce, Mongodb etc and programming languages like Java, Scala, Python and build and maintain search related product using technologies including Lucene and Elasticsearch.
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Experience with large scale enterprise applications using big data open-source solutions such as Spark, Kafka, Elastic Search / Solr and Hadoop, HBase. - Familiarity with data warehousing platforms and data pipeline tools such as Redshift, Snowflake, SQL Server, etc.
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Perform data analysis using R, statistics and data analysis, predictive analytics using SAS, and big data analytics and computer programming. Performing data analysis using R, statistics and data analysis, predictive analytics using SAS and computer programming; 3.
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Built with brands capable of reaching more than 100 million viewers in a single weekend, FOX Sports includes the sports television arm of the FOX Network; FS1, FS2, FOX Soccer Plus and FOX Deportes, as well as a joint-venture business in the Big Ten Network and digital properties including and the FOX Sports App. FOX Sports has delivered the most watched television program, NFL's America's Game of the Week on FOX, for fourteen consecutive years.
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Platforms: Experience with big data technologies like Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc. Strong understanding of big data technologies such as Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc.
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Experience using big data technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, pySpark) Research and evaluate new technologies in the big data space to guide our continuous improvement.
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Enter all the Elemental data for all BTN+ events to deliver events from the universities or network partners to our streaming platform for streaming distribution and delivery. Follow a detailed daily schedule to bring in, fax, and record of all Big Ten Conference sporting events, press conferences, and breaking news events.
ExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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This spans all data engineering at Kin from data intake, data management, data modeling, data science infra (model lifecycle management) and data ops. Being a thought leader on best practices in data engineering and having a nuanced understanding of data science and AI applications.
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big data jobs Title: manager product in Chicago, NV, Germany
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