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USEReady is looking for a Sr. Data Governance Product Owner to lead the IDQ/EDC/Axon/DGDC team for the design, development & deployment of Data Quality and Data Governance deliveries.
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Tasks could include, but are not limited to data quality review, instrument quality control review, data storage and organization, sample batch submission, training collaborators on mass spectrometry software, and data review with collaborators.
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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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Proactively identify opportunities for process improvement and optimization to enhance data reliability, quality, and accessibility. Azure Integration: Work with Azure services such as Azure Data Factory, Azure Databricks, and Azure SQL Database for data integration, processing, and storage.
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Expertise in building data pipelines and ETL processes using DataBricks, dbt, and Python. Design, develop, and maintain scalable data pipelines and ETL processes using Databricks, dbt, and Python.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Experience working with large datasets and big data technologies, preferably cloud-based (e.g., Redshift, Databricks, Azure SQL Data Warehouse, MongoDB). Design and implement data integration solutions, leveraging ETL/ELT tools such as Apache Spark, Informatica PowerCenter/BDM, and SSIS.
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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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Key data sources are eSystems used within the Quality Management System such as Trackwise, onePLM, SLMS, Quickbase and QARAD. Primary tools used by the team include Azure Data Factory, Databricks, Azure Dev Ops and Power Platform.
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Develop and implement data ingestion, transformation, and validation processes to ensure data quality, consistency, and reliability across various healthcare datasets. The ideal candidate will be responsible for designing, implementing, and maintaining data pipelines, while ensuring the highest levels of performance, security, and data quality.
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Cloud-native data platforms, services, OSS options for at least some of: data ingestion (from messages buses, databases, APIs), processing (batch, streaming), orchestration, storage, serving, cataloging, quality monitoring.
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Proven in-depth experience in designing, developing, and implementing Data Management, Data Governance, Data Process, Data Quality, and Data Migration/ETL solutions.
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Identify data discrepancies and data quality issues, and work to ensure data consistency and integrity. The Data Warehouse Architect role involves strategically designing and implementing data warehouses, data marts, and data stores as well as requisite ETL (Extract, Transform, Load) and visualization (reporting) development while ensuring high levels of data availability.
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Work as the liaison between Engineering, technology and procurement teams on development and optimization of product data across multiple systems / processes with focus on data quality, integrity and governance.
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The Data Warehouse Architect will also evaluate and provide input on infrastructure components such as software, hardware, database management systems, and networking capabilities. · Assess and cultivate long-term strategic goals for data warehousing in conjunction with IT architect(s), data users, department managers, clients, and other key stakeholders.
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data quality jobs Title: developer Company: Deloitte in Dallas, TX
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