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A robust understanding of core data engineering topics – ETL vs ELT, structured and unstructured data, data quality and data governance. The teamThe US data engineering chapter is a professional practice of data and data quality engineers.
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Providing administration support for Informatica EDC/Axon, CGDC, Metadata Command Center, Data Quality and Cloud Data Quality which includes installation, configuration, upgrades, and business continuity support.
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Build processes to help identify and improve data quality , consistency and effectiveness. Experience with AWS cloud services : EC2 , EMR, RDS, Redshift , Modern data platforms, Snowflake , dbt , Fivetran and Airflow.
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Knowledge of data process modelling for an enterprise and business function-specific data architecture (conceptual, logical & physical) designed for scalability, consistency, integrity, and quality Knowledge of data governance framework that establishes, develops an Enterprise Data Management (EDM) framework that aligns with the overall enterprise data governance policies.
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Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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The Principal Product Manager for Data & AI Governance will lead the charge for roadmap execution delivering the capabilities Privacy, Security, and Data Governance professionals use to understand, control and protect their sensitive data.
$241,875 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Interpreting and delivering impactful strategic plans improving data integration, data quality, and data delivery in support of business initiatives and roadmaps. Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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The Artificial Intelligence & Data Engineering team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making.
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Your expertise in ServiceNow ITOM (Service Mapping, Discovery, Event Management, and CMDB) will be crucial in delivering high-quality services and solutions to our clients, ensuring their business processes are streamlined and optimized.
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Skills: MarTech tools / knowledge, Adobe Analytics, Fullstory, Qualtrics, Microsoft Power BI, customer and network data, Digital Data Analytics, Adobe Audience Manager (DMP) This candidate needs to use data analytics & modeling skills to analyze digital, operational, session replay, VOC, customer call center, and other data sources to deliver Insights that will improve digital experiences at UPS. He/She will need to understand how audiences are created in Adobe Audience Manager (DMP), and how to leverage these audiences for robust Insights.
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Familiarity with recommending data governance best practices including MDM, security, privacy and policies. 5+ years of experience implementing with a variety of on-premises and cloud data management, integration, visualization, and analytical technologies.
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In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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Experience with AWS (Redshift, S3), Databricks, and ETL processes for data management and cloud integration. Expertise in Tableau, Power BI, and Alteryx for data visualization and automation.
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This position operates as the data quality assurance specialist and impact analyst for the Head Start/Early Head Start Program and supports implementation fidelity in all ERSEA areas. The CQI Coordinator will be responsible for implementing quality improvement initiatives, conducting audits, analyzing data, and collaborating with cross-functional teams to identify areas for improvement across all content areas.
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Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, and data visualization tools. Currently, we are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, data analysts/data scientists, and machine learning engineers for full-time positions with clients.
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data quality jobs Title: data manager clinical in Atlanta, CA, Canada
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