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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 Blockchain team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity on the blockchain.
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Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs, as well as to continually improve the operations, monitoring and performance of the data warehouse.
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Working closely across groups, such as the product, engineering, data science, and external partners for data modeling, general management of data life cycle, data governance and processes for meeting regulatory and legal requirements.
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Being a domain expert on data modeling, data pipelines, data quality and data warehousing. 4+ years of professional data engineering experience. Experience in building scalable infrastructure to support batch, micro-batch or stream data processing for large volumes of data.
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What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the ETL/ELT pipelines and data warehouse that is used for financial and regulatory reporting.
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Internal knowledge of open source or related big data technologies. Collaborating with business teams on the design, deployment and continuous improvement of the scalable data platform that ingests, stores, and aggregates various datasets, including data pipelines, platforms, and warehouses, and surfacing data to both internal and customer-facing applications.
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Enabling data analytics and visualization tools to extract valuable insights from the data to enable data-driven decisions. For Senior Data Engineer (III) 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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Experience with financial or compliance data, bonus if in similar business domains, such as payment systems, credit cards, bank transfers, blockchains, etc. Experience in data provenance and governance.
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Azure Cloud: Azure SQL Database, Azure Data Lake, Azure Data Factory (ADF), Azure SQL Data Warehouse, Azure Service Bus, Azure analysis service (AAS), Azure Blob storage, Azure Search, Azure App service, Redis cache using pipeline and SSIS, infrastructure as a service(IaaS), Database as a service (DBaaS), Data Migration service (DMS.
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Our current data stack includes the following tools/systems: PostgreSQL, Snowflake data warehouse, Stitch, Fivetran, dbt, Looker, Segment. Strong knowledge of key data modeling and data warehouse design approaches, appropriate use cases, their strengths and weaknesses.
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Experience implementing and maintaining data platform core services (data lake, data integration, data warehouse) and configuring and integrating infrastructure and PAAS (e.g., Azure Data factory, Informatica cloud services, Databricks, Data gateway and Qlik Sense, Power BI.
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Hands-on experience working with Azures PaaS offerings such as Purview, Databricks, Azure Data Lake Storage, Data Factory as well as monitoring of the environments. Implement data engineering, ingestion, and curation functions on Azure cloud using Azure native programming.
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As a Senior Data Platform Engineer on the MMA IT Data and Analytics Team, we will count on you to design, monitor, build, and automate data pipelines. Learn more about what makes us different and how you can thrive as a Senior Data Platform Engineer at MMA.Marsh McLennan Agency (MMA) provides business insurance, employee health & benefits, retirement, and private client insurance solutions to organizations and individuals seeking limitless possibilities.
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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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You will construct semantic layers for Looker, MicroStrategy, Tableau, and In-House Tools on top of our big data warehouse, making sure the data is represented to analysts in an accurate, consistent, and performant way.
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data warehouse jobs Title: data scientist Company: Abbott Laboratories
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