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Applying knowledge and relevant work experience in Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development tools (tools: IICS/AWS Glue/Matillion/Abinitio SSIS/SnapLogic); preferable in P&C/L&A Insurance data warehouse.
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You will assist clients in choosing a platform, defining their data needs and migrating them to a modern cloud data environment using cloud providers such as Azure, Google Cloud Platform, Amazon Web Services, Snowflake, Databricks or Teradata.
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Implementing cloud data architecture and data integration patterns for one or more of the cloud providers (AWS Glue, Azure Data Factory, Event Hub, Databricks,Snowflake etc.) Understanding of enterprise data concepts such as Master Data Management Data Governance and Enterprise Data Warehouse.
$202,000 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Understanding and thorough knowledge of Data Warehousing concepts (normalization, OLAP, OLTP, Vault data model, graphs, star & snowflake schemas); Understanding and familiarity of one or more is a big plus - CI/CD, cloud devops, containers (kubernetes/Docker, etc.
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Understanding and experience with modern cloud data architectures and engineering for one or more of the following cloud providers - AWS, Azure, GCP; We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology.
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Design and develop scalable data warehouse solutions that meet the organization’s data storage, retrieval, and analysis requirements. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
$202,000 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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You’ll focus on aligning client data strategies to their business strategy. A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics.
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Understanding of insurance data, underlying KPIs and how they are used; and, Specialty/Competency: Data, Analytics & AI. To help us achieve this we have the PwC Professional; our global leadership development framework.
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To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law.
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Demonstrating relevant project management experience in organizing and leading teams including Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development (tools: IICS/AWS Glue/SAP BODS/ SSIS/SnapLogic); preferable in P&C Insurance data warehouse.
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Being highly organized; Proven track record of implementing cloud data architecture and data integration patterns (AWS Glue, Azure Data Factory, Event Hub, Databricks, etc.) Implementing enterprise data solutions concepts such as Master Data Management, Data Governance and Enterprise Data Warehouse.
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Understanding and experience with modern cloud data architectures and engineering for one or more of the following cloud providers - AWS, Azure, GCP; Implementing cloud data architecture and data integration patterns for one or more of the cloud providers (AWS Glue, Azure Data Factory, Event Hub, Databricks,Snowflake etc.
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Big data technologies like Hadoop (Hortwonworks, Cloudera, Azure HDInsight, Amazon EMR), Spark, Kafka, Elasticsearch and others; e web, service, data, and infrastructure) and insurance specific (i.e. Guidewire, EIS, Duck Creek, etc.
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Cloud based data and analytics native PaaS components in Azure, Google Cloud, AWS. Data architecture, data modeling and data management across relationship, columnar and noSQL technologies like SQL Server, MongoDB, Vertica, neo4j.
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Understanding of Data Warehousing concepts (normalization, OLAP, OLTP, Vault data model, graphs, star & snowflake schemas); Possessing understanding and experience with modern cloud data architectures and engineering for one or more of the following cloud providers - AWS, Azure, GCP.
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big data jobs Company: Pwc in Fernley, Nevada
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