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The main technologies we use include: Elixir, Erlang, Python, Terraform, Ansible, Packer, EMR/Spark, Apache Spark, Apache Druid, BigQuery and Redis. Knowledge or experience with big data technologies such as Spark, Hadoop, Redshift, Snowflake, Kafka, Flink, Druid, Clickhouse.
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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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Experience with big data technologies (e.g., Databricks, Hadoop, Spark) and cloud platforms (e.g., Azure, AWS) is a plus. ex., Databricks, Hadoop, Spark) et avec les plateformes de nuage (p.
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Data Warehousing, Data modeling, Data mastering, Data quality, ETL, Informatica, Alteryx, MSSQL, Oracle, Teradata, Hadoop, Snowflake, MSSQL, SSIS, SSRS, PowerBI, Tableau, Python, R, Scala, SPARK a další programovací jazyky, reporting, ETL nebo další datové nástroje.
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Data warehousing and integration tools (e.g., Fivetran, Apache Spark, Informatica) is a leading digital health company that connects patients, healthcare providers and life sciences companies with the right information in the moments care decisions are made.
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Exposure to data engineering coding languages such as Python, R or Spark. 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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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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Experience in big data technologies(Apache Hadoop/Spark/Hive/Presto) Proficiency in Apache Spark & Apache Kafka. Good exposure to SQL (T-SQL/PL-SQL/SPARK-SQL/HIVE-QL). You’ll work with a team of world-class talent from Stanford GSB, Wish.com, D.E. Shaw, Stitch Fix, Urban Outfitters, Wayfair, McKinsey, Nike etc.
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Sie verfügen über Erfahrungen mit relationalen Datenbanken (on-Premise wie cloudbasiert) und über Kenntnisse in Datenanalysesprachen oder -tools (Python, R, SQL, SAS, R, Python, Spark o. Sie unterstützen bei Ad-Hoc-Analysen und Analytics-Anforderungen (Python, R, SQL, SAS, R, Python, Spark o.
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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) Develop data cleaning and data checking pipelines using Spark SQL/Pyspark on Databricks.
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Design, develop, and deploy Spark program in databricks environment to process and analyze large volumes of data. A multinational organization with 48 offices in 19 countries and the possibility to work abroad.
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Good understanding of data pipeline design concepts, Hands-on experience with Postgres and Snowflake, Excellent coding skills in Python, Experience with Apache Airflow and Apache Spark tools, Knowledge of AWS, Experience with CI/CD tools and processes, Good communication skills.
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Experience with big data frameworks and tools, such as Spark, Hadoop, Kafka, Hive, and Airflow. You will work with cutting-edge technologies and tools, such as Spark, Kafka, AWS, Azure, and Elastic, to handle large-scale and complex data challenges.
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O Familiar with the following tools: Python, Python libraries (Pandas), Py Tests, SQL, NoSQL, MySQL, Apache Spark, ETL, Cloud tools: Azure, Google & AWS (e.g. S3 buckets, Glue, Redshift), Data Lakes, GitHub. PowerBI, Tableau, Snowflake, Apache Airflow.
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Technical Skills : Proficiency in Python, data modelling, Snowflake, SQL, dbt, Airflow, Spark, Machine Learning, Data Analytics, & AWS. Healthcare (including Vision and Dental) and Additional Benefits.
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star tribune healthcare spark jobs in Snowflake, AZ
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