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Strong technical proficiency to contribute to data engineering task in an AWS and Databricks ecosystem. You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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Azure Data lake Gen2, ADF, Azure SQL DB, SQL Server, Oracle etc. Previous experience as an Architect with hands on working experience on Databricks, Spark, Kafka, Snowflake.
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Senior Data Engineer (Python, Kafka, Databricks, AWS) 3+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.
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Job Req ID: 24641 About Supermicro: Supermicro is a Top Tier provider of advanced server, storage, and networking solutions for Data Center, Cloud Computing, Enterprise IT, Hadoop/ Big Data, Hyperscale, HPC and IoT/Embedded customers worldwide.
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Proficient in data platforms/systems (such as SQL, Databricks), ETL tools (such as Python, SnapLogic), process automation, and standardization. Manage data transitions and platform migrations between SAP HANA/DataBricks, Tableau/PowerBI, and related ETL processes.
$73,900 - $170,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Proficient in project software such as SAS/SQL, Python/PySpark, Snowflake, R, Databricks CMS cloud environments. Manipulates and extracts Medicare, Medicaid, and other healthcare claims data stored in Cloud environment using appropriate software such as SAS, Snowflake, Python, R, SQL, and other software as appropriate for the task.
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New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Data Engineer. As a Capital One Data Engineer, you'll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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Qualifications Requirements: Bachelor's degree inputer Science, Information Technology, or a related field Solid experience in Databricks platform, data engineering, and using Delta Live Tables Experience with medallion architecture in a data lake environment Proficiency in Snowflake data warehousing platform Strong understanding of ETL workflows and data pipeline automation.
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Experience with distributed data and computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka. As a big data engineer at Booz Allen, you'll implement data engineering activities on some of the most mission-driven projects in the industry.
$75,600 - $172,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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MUST HAVE minimum 3 years of hands-on experience of SQL in Hive/Hadoop/Google Cloud Platform environments. Need to have : - Python - SQL - Tableau or PowerBI or other dashboarding tool - Marketing or Digital Media focus.
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The ideal candidate for this role is a well-rounded top performer with exceptional data engineering, analysis, and visualization skills, capable of driving growth in a fast-paced environment. In this role, you will have the opportunity to help drive Adobe’s pivotal initiatives by data engineering solutions that connect systems to visualization platforms for management reporting.
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Azure Data Bricks, Azure Data Factory, Azure Datalake, Python, SQL, PowerBI. Strong databasee background with Oracle and SQL Server are also important. Design, develop, and maintain ETL processes using Databricks, Python, and SQL.
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Knoledge in Databricks, PowerBI, programing languages including SQL, Python and PySpark, data principles including data pipeline, streaming data, data storage, ETL, data integration, database design Leadership (Vision, strategy and business alignment, people management, communication, influencing others, managing change.
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Hands-on experience with On-prem & cloud data platforms such as Snowflake, AWS Redshift, Azure Synapse Analytics, Databricks, AWS Aurora, Oracle Exadata, SQL server, Hadoop, Spark, SAS and R.
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