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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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Analyze construction quality related data from a variety of sources including audit logs, nonconformance logs, contract review logs, audits conducted by IQA, PHMSA, and similar data.
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Identifies through extraction errors or concerns in workflow and works with the coding department to improve data quality and coding on MIPS and other key quality, operational or patient flow When noted, the Clinical Quality Coder I will correct quality errors and stat code errors in the system to improve data integrity in facility dashboards and provider scorecards.
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Under supervision of a mentor/coach, performs the following tasks: interpretation of FDA, regulations; project management; regulatory guidance review; quality issue investigations; and QA data collection, trending and analysis.
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Broad experience desired, but not essential, in multiple domain areas, such as data warehousing, business intelligence (BI), data governance, data architecture, data integration, data classification, data strategy, data quality management, data security and privacy, MDM, data standards, regulatory compliance, and enterprise architecture frameworks.
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Maintains oversight of environmental testing program, with data review in eBacMap, in coordination with QA Supervisor. The QC Supervisor is responsible for overseeing the day-to-day operations of QC Technicians and ensuring compliance with all food safety and food quality programs.
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Experience with CI/CD, containerization (ex: docker, K8s) and orchestration (ex: Airflow) Experience building production systems with more modern ETL, ELT and data systems, such as AWS Glue, Databricks, Snowflake, Elastic, and Azure Cognitive Search Experience deploying data infrastructure on cloud platforms (AWS, Azure, or GCP) Strong knowledge of data quality, data governance, and data security principles and practices Excellent communication, collaboration, and problem-solving.
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Responsible for understanding the various data sources available within IEHP for reporting and analysis, as well as a clear understanding of IEHP business operations to be able to appropriately guide the development of quality program activities, including analysis and reporting.
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Implement and manage data transformations with DBT for quality assurance. This role requires expertise in PySpark, Airflow, DBT, and Databricks to drive high-performance data processing and analytics.
$210,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Demonstrated experience in leading data migration projects, implementing data governance, and enhancing data quality across enterprise systems. Advocate for and implement data quality governance and standardization across enterprise systems, significantly enhancing data integrity and reliability.
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The Manager Credentialing/Provider Data Management will be responsible for the administrative aspects for all credentialing functions needed to meet health plan and accrediting body requirements including but not limited to National Committee for Quality Assurance (NCQA) and CMS. This role, in combination with the Credentialing team is to maintain procedures and processes in line with all regulation and compliance requirements.
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Develop and implement strategies, best practices, and standards for data engineering, including data modeling, data integration, data quality, and data governance.
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DPS Group is seeking a qualified Senior Quality Assurance Operations professional to perform batch disposition, batch record review, deviation, CAPA and change control support at the Boston, MA client site.
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The relevant infrastructure will include elements such as an enterprise data catalog, data governance (including conventions and standards), data quality, master data management, application integration, data exchange, ETL/ELT, data modeling, and related components.
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The Clinical Data Analyst partners cross functionally to identify risk to data integrity throughout the data flow to drive quality collection for non-EDC data sources (fluid & tissue labs, digital, imaging, wearables) in Dyne's clinical studies.
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data quality jobs Company: Enterprise Mobility in DC, Germany
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