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Big Data implementation using Open Source and NoSQL technologies such as Databricks, Spark, Spark Streaming, Kafka, Storm, Zeppelin, Scala, Software development, Hadoop Hive, Hadoop Map Reduce, Hadoop Clusters, Cosmos DB, Azure Data Lake Storage (ADLS.
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Hands-on experience building data pipelines using Hadoop components Sqoop, Hive, Solr, MR, Impala, Spark, Spark SQL., HBase. 4-5 experience building data pipelines using Hadoop components Sqoop, Hive, Solr, MR, Impala, Spark, Spark SQL., HBase.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Experience in ETL, SQL, Informatica, Power exchange, Databases like SQL server, DB2, Oracle.
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Big Data Technologies: Proficient with big data technologies such as Databricks, Hadoop, Spark, and Kafka. Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Experience with one or more SQL-on-Hadoop technology (HIVE, Presto, Spark SQL, Databricks) and Hadoop ecosystem. Hands on experience in data engineering desired with extensive knowledge of SQL and PySpark, on Databricks Platform.
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Design, develop, and implement data architecture solutions using SQL Server, Microsoft Azure, Snowflake, and Databricks. The ideal candidate will have extensive experience in designing and implementing data solutions, with proficiency in SQL Server, Microsoft Azure, Snowflake, Databricks, and other relevant technologies.
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Must Have skills: MDM, Experience in writing queries (SQL, Python, R, Scala) as needed and experience with various data technologies such as Azure Synapse or SQL Server, Data Modeling, Snowflake, Databricks.
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Required 10 Years Hands-on experience with Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure SQL, Azure Synapse Required 5 Years Hands-on experience in SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL Required 10 Years Hands-on experience in Azure SQL Database, Azure SQL Datawarehouse Required 7 Years Hands-on experience in deploying and maintaining large-scale data processing pipelines.
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5+ years in designing, solutioning the Databricks, Snowflake, PySpark and Big data tools including DataOps, Data engineering, Data Integration, Data Orchestration and Data Marketplace. Relevant certifications (e.g., Snowflake, Databricks, Certified Analytics Professional, AWS Certified Big Data - Specialty) are a plus.
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. - High level of proficiency in ETL processes and demonstrated hands-on experience with technologies such as DataBricks, Python, Spark, Scala, JavaScript/ JSON, SQL, and Jupyter Notebooks.
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You will have indepth knowledge and experience in; cloud data lake house; Databricks (preferred) or Snowflake; cloud-native solutions knowledge; SQL or Python; modern DevOps approach; have written data code AND also the CI/CD pipelines.
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Net, SQL Server/SSIS/SSAS Reporting tools Angular / React Azure DevOps Visual Studio Azure DataBricks, Data Factory Domain experience : Working knowledge of Investment Securities Trading, Operations, Compliance workflows & Analytics) Designed and developed the applications using Agile Scrum methodology.
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Job Title: Data Engineer/ Data ArchitectLocation: Corvallis, OR – 5 Days Onsite Role Job Description: At least 8 to 10+ years’ experience in data engineering , AI and ML and Aws/Azure Architect, Design and implement distributed data processing pipelines using Spark, Python, SQL and other tools and languages prevalent in the Big Data/Lakehouse ecosystem.
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Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, Databricks, EMR. Experience with data warehouse platforms such as Redshift, Databricks, Big Query, Snowflake.
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Expert in applying SCD types on S3 data lake using Databricks/Delta Lake. AWS/Kafka/Databricks or similar certifications. Expert knowledge in writing complex pySpark, SQL, dbt and ETL development with experience processing extremely large datasets.
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databricks hadoop sql server engineer jobs Company: U S Bank
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