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Preferably, relevant certifications in data architecture and related technologies (CDMP, TOGAF, GCP Professional Cloud Architect, AWS Certified Solutions Architect, Azure Solutions Architect, Snowflake SnowPro Core Certification, etc.
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Experience implementing solutions using at least one of the following technologies Azure Data Factory, Azure Event Hubs, Azure Data Lake Storage, Azure Function Apps, Azure Synapse Analytics, AWS Glue, AWS S3, AWS Lambda Functions, AWS Redshift, Databricks, Snowflake, Google Big Query, Alteryx, SSIS, Informatica.
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Familiarity with big data platforms, such as Azure Databricks, Azure HDInsight, or Azure Stream Analytics. Your proficiency in data modeling, database design, and data warehousing will serve as the bedrock for pioneering innovations, coupled with hands-on experience across various data sources and platforms, with a specific emphasis on Microsoft Azure.
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Knowledge or experience with big data technologies such as Spark, Hadoop, Redshift, Snowflake, Kafka, Flink, Druid, Clickhouse. As part of the backend team you will be working on challenging problems within highly distributed services, and also real-time streaming and batch data processing.
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Impatient, tu souhaites profiter de ton stage pour monter rapidement en compétences sur différents langages et outils d’analyse de données et de data visualisation : Python, SQL / Big Query, Google Analytics 4, Looker Studio, Tableau, Power BI.
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Experience with big data technologies (e.g., Databricks, Hadoop, Spark) and cloud platforms (e.g., Azure, AWS) is a plus. data visualization tools (Power BI, Tableau) Strong knowledge of statistical techniques, machine learning algorithms, and data mining techniques.
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Build and maintain big data ETL pipelines using DBT and Airflow. This is an exciting opportunity to work with high volume, high velocity streaming analytical data and to build data pipelines using Google Composer and manage and maintain Data warehouses and Data lakes on Big Query and Snowflake.
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Expertise with Big Query, Google Cloud Storage,Cloud Composer,Kubernetes,Cloud Logging,Bitbucket, Dataflow or Apache Airflow. Experience in creating Data pipelines using Google Cloud Composer or Apache Airflow.
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Broad expertise and experience with distributed systems, streaming systems, and data engineering tools, such as Kubernetes, Kafka, Airflow, Dagster, etc. Deep knowledge of Python, SQL, database design, and master data strategies.
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This role will primarily focus on Looker and BigQuery, and the ideal candidate will have a strong background in data engineering, SQL, and data modeling. 3-4 years of experience in data engineering and working with Looker and BigQuery.
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You will also be working closely with Cloud, Big Data, Data Modeling, and Project Management consultants. Experience with developing and supporting data management environments utilizing tools such as Tableau, Power BI, TIBCO, MSBI, Informatica, and Databricks.
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Une approche technique (Data Platform), pour déployer des projets d’architecture data chez nos clients à l’aide des meilleures technologies (Azure, Snowflake, Big Query, etc.) Expertise: nous nous engageons, avec passion et franchise, dans l’expertise Data et les projets numériques.
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Data Integrity ("DI") is responsible for data management, data governance, and data quality consumed by the functions within FRM. DI leverages tools to manage data quality based on logical rules and thresholds across one or more of the following dimensions: accuracy, completeness, conformity, consistency, coverage, duplication and timeliness.
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Experience working with at least one of the following Modern Cloud Native Data Warehouses (AWS Redshift, Snowflake, BigQuery) Proficiency with using data visualization tools such as Tableau, Looker, PowerBI or similar platforms.
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Designing and developing Azure-based data solutions using Azure Data Factory, Azure Databricks, Azure SQL Database, and Azure Synapse Analytics. Databricks, Snowflake, Python and Data Modelling skills.
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big data jobs Title: data manager Company: Rackspace Us in Snowflake, AZ
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