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Improve the quality of data and usability by driving an understanding and adherence to the principles of data quality management including metadata, lineage, and business definitions.
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As Principal HR Data Analyst, this hands-on role will drive HR data discovery and collection, data security, data cataloging, data transformation, data analysis, data visualization, and reporting in support of the organization’s overall HR Data & Reporting objectives.
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Your responsibilities will include: - Developing data visualization solutions using tools like Tableau, Power BI, and/or Qlik - Cleaning and reviewing data scripts using Python and other tools - Creating additional data visualization capabilities as needed - Ensuring data quality standards are met - Developing training materials - Analyzing current processes and suggesting improvements - Organizing and leading client meetings - Summarizing and presenting information and reports to the team.
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May recommend data analytics strategies including enterprise data warehousing, master data management, data quality, data governance, Big Data, business intelligence, visualization.
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Perform data cleansing, data integration, and data quality assurance activities to maintain the accuracy and integrity of large datasets. Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis.
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Understand the concepts supporting relational databases, data warehousing, data governance, data access, data quality and related areas. Provide guidance to coworkers on business and technical issues affecting projects, such as data access, data quality, storage capacity, and analytic tools and software.
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The data engineer reports to the Systems Manager and works with the team in developing and supporting high-quality, secure systems and data pipelines. The Smithsonian Institution’s Office of Advancement seeks a Data Engineer to serve as a key member of the Advancement Technology Services team as we transform our data management approach.
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Design and implement data integration and migration solutions, perform gap analysis across systems, ensuring data quality, integrity, and compliance throughout the migration process.
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We integrate off-the-shelf and new development efforts to sustain and enhance Defense Intelligence Agency’s (DIA) National Media and Exploitation Center (NMEC) architecture by leveraging cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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Develop and implement data quality procedures: Develop and implement procedures to ensure the accuracy and completeness of our data. Experience with cloud computing platforms and data warehouse solutions such as AWS, Azure, Snowflake, and Microsoft SQL Server.
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Our areas of expertise include:Managed Care & Care Value | Care Delivery Model Transformation Implementation | Care Management | Quality Improvement & Patient Safety | Program Management & Change Management | Program Evaluation & Data Analytics | Organizational Development & Strategic Planning.
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You will be involved in understanding digital asset trading and transaction data (across equities, commodities, fiat, cryptocurrency, etc.) As a data and implementations analyst, you will work closely with our Subject Matter Expert (SME), engineering and product management teams to understand and work across all areas of our public sector client solutions.
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Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks. Understanding of data modeling/visualization, database design principles, and data governance practices.
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Guidehouse is looking for a Data Scientist to join our team in the Defense and Security Segment. Designing and developing data visualizations and dashboard solutions. Data Science Consulting.
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Experience utilizing software programs related to electronic batch records (ERBs), electronic quality management systems (QMS), laboratory information management systems (LIMS or MODA), building automation systems (BAS), manufacturing monitoring systems (MMS/PI), supervisory control and data acquisition (SCADA, PI-Historian), and enterprise resource planning (ERP.
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data quality jobs Title: data specialist Company: Officeteam in Washington, DC
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