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In architecture, design and development of data integration (ETL) solutions, including data quality and master data management - primarily using Microsoft technologies; + Data Integration: SSIS, Azure Data Factory, Databricks, or other enterprise ETL tools.
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Prepare data for model training, validation, and testing using data cleaning, transformation, augmentation, and visualization techniques to improve data quality and utility for AI and ML models.
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Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
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In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies. Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire.
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Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing. Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep.
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Must have experience in architecting and implementing data architecture, data engineering, reporting and analytical solutions across multiple business functions and domains. Experience deploying enterprise-wide reporting solutions while leveraging data visualization best practices.
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Data Strategy and Governance. Should also be able to Identify the implications for data governance that arise from the technology, current processes, and skill levels in a complex data environment.
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Identify data governance gaps and assess data governance maturity in a complex data environment. Ideal candidates may call themselves Data Architects, Data Engineers, Data Scientists, Analysts and Data Governance professionals.
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Our Data Science Team provides code development, data source identification, data testing, advanced statistical methods and best-practices for advanced modeling techniques for our Labor Workforce Allocation, Annual Operating Plan, and Long-Range Plan. We maintain Data Quality Standards and Data Governance, Accessibility, Storage and Scalability – all the while developing analytical methods and applications that unlock the monetary value of data assets.
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The GPS AI & Data Engineering offering is responsible for developing advanced analytics products and applying data visualization and statistical programming tools to enterprise data in order to advance and enable the key mission outcomes for our clients.
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Authors and manages currency of Configuration Management Plans (CMP) for Sustainment and EMD programs; researched and revamped documents to include data engineering, data integration, data quality, and security.
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The Sr. Supplier Quality Engineer shall support the business in the areas of Supplier Project Management for assigned commodities, Supplier Assessments, Supplier Performance Improvement, Technical Data Interpretation/Analysis (engineering drawings, specifications, technical publications, purchase orders, etc.
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Ascend Performance Materials is the premium provider of high-quality chemicals, fibers and plastics. Ascend Performance Materials is the premium provider of high quality chemicals, fibers and plastics.
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Implement and manage continuous integration and continuous testing practices, emphasizing ETL job automation, SQL query validation, and Snowflake target validation for ongoing data quality and reliability.
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Develop, optimize, and oversee autonomous vehicle data infrastructure, including the creation and management of software tools, data catalogs, and robust data pipelines that facilitate efficient data extraction, transformation, and delivery of high-quality data products for internal use and stakeholder presentation.
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data quality jobs Title: data specialist Company: Kelly Services
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