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Performs analyses, development, and evaluation of data mining in the Snowflake cloud data warehouse environment which includes data design, database architecture, and data management utilizing Informatica PowerCenter, Intelligent Data Quality, and Enterprise Data Catalog.
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Etc into pyspark Strong knowledge of cloud native data platform architectures, data engineering and data management Good knowledge of popular database and data warehouse technologies from Snowflake Microsoft Azure SQL Data Warehouse Demonstrated knowledge of data warehouse concepts.
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The MA Data Ops Developer will be responsible for building, enhancing, maintaining and automating data warehouse structures as well as owning data inflows and outflows that support the Medicare Advantage Risk Adjustment teams and efforts.
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3+ years’ experience with a cloud data lake/warehouse solution (SQL Server, Snowflake, Databricks, Azure Data Warehouse, etc. Proven experience as a Data Engineer, working with large-scale data pipelines, data warehouse architecture, and ETL processes.
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The Data Solution Architect must have familiarity with traditional data technologies (Data Warehouse, Data Lake) as well as transformative capabilities such as Data Lakehouse, Data Fabric, and Data Mesh in order to define go-forward strategies which are compliant for US Govt clients – including addressing Federal Cloud security requirements, data privacy, data security, and data integration approaches which are approved for US Govt use.
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Experience in Data Migration from RDBMS to Redshift/Snowflake cloud data warehouse. Provide direction on adoption of Cloud technologies (Redshift, Postgres, Snowflake,) and industry best practices in the field of data lakes and data warehouse architecture and modelling.
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Store Supply Warehouse has an immediate need for a Full Time, Day Shift Warehouse Worker (Forklift Operator). As a Warehouse Worker (Forklift Operator), you will be part of the order picking process, shipping and receiving, loading/unloading, and other duties in a fast-paced environment.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting.
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Collaborate with the Finance or MP&L Application owners and the Ingestion team to “Land” and “Transform” the data in the Data warehouse on GCP BigQuery. Create data warehouse objects of raw data, and Analytical Model objects which are data products of customized data environments in GCP BigQuery (Data Warehouse), crafted to facilitate access of the information, with the goal of supporting scalable growth, sustainability, reusability, faster analytical solutioning and to accelerate delivery of business value.
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Sports Warehouse is comprised of: Tennis Warehouse Running Warehouse Tackle Warehouse Total Pickleball Racquetball Warehouse Riding Warehouse Inline/Ice Warehouse Skate Warehouse.
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Continually improve the operations, monitoring and performance of the data warehouse. 4+ years of professional data engineering experience. Being a domain expert on data modeling, data pipelines, data quality and data warehousing of financial data.
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Experience in building scalable infrastructure to support batch, micro-batch or stream data processing for large volumes of data. Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs.
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Internal knowledge of open source or related big data technologies. Circle is a financial technology company at the epicenter of the emerging internet of money, where value can finally travel like other digital data — globally, nearly instantly and less expensively than legacy settlement systems.
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Collaborating on the design, deployment and continuous improvement of a scalable data platform that ingests, stores, and aggregates various datasets. Experience with financial data, bonus if in similar business domains, such as payment systems, credit cards, bank transfers, blockchains, etc.
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Collaborate with the Finance or MP&L Application owners and the Ingestion team to Land and Transform the data in the Data warehouse on Google Cloud Platform BigQuery. Create data warehouse objects of raw data, and Analytical Model objects which are data products of customized data environments in Google Cloud Platform BigQuery (Data Warehouse), crafted to facilitate access of the information, with the goal of supporting scalable growth, sustainability, reusability, faster analytical solutioning and to accelerate delivery of business value.
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data warehouse jobs Title: data scientist Company: Ibm
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