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Minimum of 7 year of designing and building production data pipelines from data ingestion to consumption within a hybrid big data architecture, using Cloud Native GCP, Python, SQL etc.
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Data Platforms: Teradata, Couchbase, MongoDB, Oracle, SQL Server, ADLS, Snowflake. 5 years data science/business intelligence/data analytics experience using common BI tools (Cognos, Tableau, etc) and demonstrating SQL mastery.
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Active Google Cloud Data Engineer Certification Hands on in designing, building and operationalizing large-scale enterprise data solutions and applications using one or more of GCP data and analytics services in combination with 3rd parties - Python, Pyspark, Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache Beam/ composer, Big Table, Cloud BigQuery, Cloud PubSub, Cloud storage Cloud Functions & Github.
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Fluent in SQL, Python, and at least one analytic tool such as OBIEE, Power BI, or Tableau is required. Solid experience with cloud data warehouse platforms such as Snowflake, Redshift, BigQuery, Synapse, Databricks, etc.
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Expertise in Data visualization tools such as Power BI, Tableau and Looker is a plusAbility to understand API Specs, identify relevant API calls, extract data and implement data pipelines & SQL friendly data structures.
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Role: GCP Data Engineer. Work with data team to efficiently use Google Cloud platform to analyze data, build data models, and generate reports/visualizations. Work with implementation teams from concept to operations, providing deep technical subject matter expertise for successfully deploying large scale data solutions in the enterprise, using modern data/analytics technologies on premise and cloud.
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Knowledge of local and wide area networking on multiple platforms: Windows, Linux, and VMware; network protocols and routing; network, server, and host operating systems; IP networking, internet, and intranet technologies; email, office automation and collaboration technologies; voice and/or data communications; voice and/or data networking; Windows desktop OS; server hardware, software, and administration.
$52.1 - $69.6 an hourExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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NET MVC, C#, Java, NodeJS, HTML, CSS, SASS, SQL Server, Oracle, MySQL, SQL, Queries, Functions, Stored Procedures, Azure Cosmos DB, MongoDB, Azure, AWS, Business Intelligence, ADF, SSIS, SSAS, SSRS, Power BI, Mobile Development Experience, Xamarin, Swift, Objective-C, CI/CD Pipeline, GitHub Actions, Azure Pipelines, Gitlab Runners.
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Ensure adherence to quality expectations and standards. It is this foundation and our belief that our culture drives success by which The Ritz Carlton has earned the reputation as a global brand leader in luxury hospitality.
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Build and maintain data pipelines and ETL processes using Python, Spark, and SQL. Strong understanding of data governance, data quality, and data security principles.
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Qualifications + years of experience in full-stack web development with hands-on expertise in React JS or Angular JS, and Deep knowledge of Azure services, including Azure Functions, App Service, SQL Server, and NoSQL databases.
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Develop and maintain data pipelines to extract data from NetSuite, load it into Google BigQuery, and process it using Python (pandas) with embedded SQL. Experience with data architecture and ETL processes, including extracting data from NetSuite, processing with Python (pandas), and loading into Google BigQuery.
$125,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Desired Qualifications:Hold one or more certifications in: Certified Information Systems Auditor (CISA), Certified Internal Auditor (CIA), Certified Anti-Money Laundering Specialist (CAMS), or Certified Fraud Examiner (CFE)Experience with automation and/or data analytics in order to assess data quality controls using tools and techniques, such as SQL, Alteryx, Python, etc.
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Predictive Analytics/Data Mining: (e.g., Python, SAS Enterprise Miner) Microsoft SQL Server, Oracle, MySQL, Hive, Spark. Data Visualization Tools (e.g. QlikView, Tableau, Power Bi.
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Create and manage data storage solutions using Google Cloud Platform services such as BigQuery, Cloud Storage, and Cloud SQL. Automate data processing tasks using Python. Google Cloud Platform - Professional Data Engineer, Google BigQuery, Hadoop Big Data Stack, UNIX Shell Scripting, Agile Methodology.
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