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Strong understanding of cloud infrastructure, services and protocols like EHRs, EMRs, Athena, Scala, Databricks, Snowflake, Spark, RDS, glue, Redshift, Apache airflow, SQS, SNS. Strong understanding of cloud infrastructure, services and protocols like EHRs, EMRs, Athena, Scala, Databricks, Snowflake, Spark, RDS, glue, Redshift, Apache airflow, SQS, SNS.
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Understanding of relational databases (e.g., Snowflake, Google Big Query, Databricks, Redshift, Synapse), data warehousing, ETL, web services, SaaS technologies, etc. Experience with BI tools (e.g., MicroStrategy, Tableau, PowerBI, Qlik, SAP Analytics Cloud, Quicksight, Business Objects, Cognos, Looker.
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Familiarity with big data platforms, such as Azure Databricks, Azure HDInsight, or Azure Stream Analytics. These technologies include but are not limited to: Microsoft, SAP, Qlik, Snowflake, Alteryx, Automation Anywhere, and Workday Adaptive Insights.
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We provideexpertise in Azure, AWS, GCP, Snowflake, Databricks, and Python. We provideexpertise in Azure, AWS, GCP, Snowflake, Databricks, and Python. You will work onvarious projects, including data governance, data quality, data integration,and master data management.
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AWS Python SQL Hadoop Spark. Hadoop, Spark, Scala, Python) Bachelor's degree in Computer Science or related field, extensive experience in front-end development with Angular, experience with SDLC and Agile/SCRUM, back-end system integration experience, UX Design experience, experience with testing frameworks, version control tools, excellent communication and interpersonal skills.
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Work with the internal partnerships team to deliver OEM (Original Equipment Manufacturer) product proposals, close data and analytics product business (ex: IBM, Tableau, Alteryx, Snowflake, Databricks, etc.
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In-depth knowledge of big data technologies such as Spark and Hadoop. 2+ years of experience working in cloud platforms such as GCP, Azure, AWS, Snowflake, and othersfor data store, data processing and data consumption.
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Technical knowledge in Spark, Hadoop & GCS Stack. Technical knowledge in Spark, Hadoop & GCS Stack. Experience with database modeling and development, data mining and warehousing. Hands on coder with good experience in programming languages like Java, Python, C.
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Practical & recent experience in data pipeline development with Big Data frameworks (Databricks, Spark, Kafka), data modelling approaches (Star schema, Snowflake, Data Vault), and Azure Services (Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
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Knowledge of common databases like SQL, Databricks, advanced excel, VBA, advanced PowerPoint, Engagement and execution data, etc. Knowledge of data warehousing, Snowflake, SQL, Databricks.
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Experience working in cloud based relational DB platforms (Databricks, Experience working in cloud based relational DB platforms (Databricks, More than 200,000 organizations worldwide trust Barracuda to protect them — in ways they may not even know they are at risk — so they can focus on taking their business to the next level.
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Steekwoorden: Angular, Sitecore, Mulesoft, Tibco, SAP, Snowflake, Databricks, QlikSense, Serverless, AWS. Ervaring met AWS/Snowflake/Databricks/Qliksense is een pré Steekwoorden: Angular, Sitecore, Mulesoft, Tibco, SAP, Snowflake, Databricks, QlikSense, Serverless, AWS.
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Knowledge of Data Engineering and the respective tools and technologies (e.g., Apache Spark, Databricks, Python, SQL DB, Data Lake concepts) As a Data Engineer on the LAPA team, you will be responsible for designing and implementing data pipelines using industry-leading cloud applications such as Databricks and orchestration tools such as Azure Data Factory.
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Building ETL processes using metadata driven frameworks based on ADF/Databricks. Designing and developing Azure-based data solutions using Azure Data Factory, Azure Databricks, Azure SQL Database, and Azure Synapse Analytics.
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Platform as a Service (Cloudera, Snowflake, Databricks), Integration et Compute (Talend, Dbt, Snaplogic, Spark, Glue. - Machine Learning : Tensorflow, Scikit learn, Kubeflow, Machine Learning : Dataiku, Azure ML, SageMaker, VertexIA, Databricks ML, Azure Cognitive Services, ML Framework (TensorFlow, Keras, PyTorch.
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