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Must have experience of working on Transactional systems, ODS, BI/Data Warehouse/Marts, ETL/Data Integration & Analytics, Big Data solutions and Client Solutions and map them to equivalent/better GCP Products.
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Experienced knowledge in data analysis using SQL, user story development, data warehouse design and modeling (3rd normal form or dimensional modeling), data integration design and development and/or performance tuning Teradata SQL.
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Experience working with large-scale data warehouse solutions such as Teradata, Snowflake, or Redshift. Solid technical database knowledge (Hadoop, Teradata, Snowflake data modeling) and experience optimizing SQL queries on large data.
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Design, develop and deliver data integration/data extraction solutions using IBM DataStage or other ETL tools and Data Warehouse platforms like Teradata, BigQuery.
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3-5 years Experience in Data warehouse and Data lake implementation. Immediate need for a talented Google Cloud Platform Data Engineer. Knowledge of data Modelling, database design, and the data warehousing ecosystem.
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Design and development of ETL data integration solutions in data warehouse environment; Relational databases and Cloud-based technologies; Design and architecture experience on large-scale ETL solutions; Work with Enterprise Data warehouse data models and dimensional modeling concepts, source to target mapping and Data Integration architecture.
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3-5 years of software development experience with very high proficiency in Python or Scala or Java and experience optimizing SQL queries on large data. Experience in building data engineering monitoring tools.
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Knowledge of Data Warehouse technology (Unix/Teradata/Ab Initio/Python/Spark/Snowflake/No SQL)Experience in migrating ETL processes (not just data) from relational warehouse Databases to AWS based solutions.
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Is required Working knowledge of test planning, test data management, automated & manual test execution, and test management tools to support complex data and cloud landscape Working knowledge with Oracle, Teradata, SQL Server, ETL tools and data warehouse architectures highly preferred Working knowledge of QA methodologies, life cycle and processes Experience in Maintaining and Managing Test Environments for Integration and End to End testing.
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Position Summary Risk and Financial Advisory - Hybrid Operate Master QA Automation Engineer - PDM Manager Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment.
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As a Master QA Automation Engineer in our Hybrid-Operate business, you'll have the opportunity to gain valuable hands-on experience, share ideas, and collaborate with leading professionals as we engage a diverse set of industries with effective solutions Recruiting for this role ends on 04/30/24.
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Work You'll Do As a Master QA Automation Engineer, you will help lead the development of quality control standards, processes, and corrective actions to ensure appropriate use of best practices and tools.
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Deloitte Transactions and Business Analytics LLP is not a certified public accounting firm. As used in this posting, "Deloitte Advisory" means Deloitte & Touche LLP, which provides audit and enterprise risk services; Deloitte Financial Advisory Services LLP, which provides forensic, dispute, and other consulting services; and its affiliate, Deloitte Transactions and Business Analytics LLP, which provides a wide range of advisory and analytics services.
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Experienced knowledge in data analysis using SQL, user story development, data warehouse design and modeling (3rd normal form or dimensional modeling), data integration design and development and/or performance tuning Teradata SQL. Knowledgeable in data warehouse market best practices, development standards and methodologies.
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Awareness of Integration tools within Azure (Azure Data Factory (ADF), Azure Data Brick, Python, Spark SQL) Overview of Work: Prepare data for ingestion to data warehouse through supporting data management, data mapping, and dataT modeling activities.
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