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As a Senior QA Automation Engineer, you will perform Quality Assurance and Automation testing for data warehouse implementations, ensuring data accuracy, completeness, and adherence to quality standards.
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Bachelor's degree in Computer Science, Data Science, Linguistics, or a related field. Assist with data consolidation and organization to create a searchable innovation knowledge center.
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Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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DataAnnotation is committed to creating quality AI. Join our team to help train AI chatbots while gaining the flexibility of remote work and choosing your own schedule. Note: Data Annotation payment is made via PayPal. We will never ask for any money from you.
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Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, Redshift, Airflow. Fluent in data exploration and visualization tools such as Looker and Tableau. Our team masters exploratory data analysis, advanced reporting, data modeling and visualizations that serve the dual purpose of driving business decision making and delivering fact-based actionable recommendations.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Build to design and develop technical/functional specifications with Kinaxis RapidResponse, and SAP Planning applications – working on different modules like Supply Planning/MRP, Forecasting and Demand Planning, ATP, Aggregate Supply Planning, Capacity Planning, Attribute Based Planning, Sales & Operations Planning with required interfaces and data management/data migration with source and target applications.
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Performs noninvasive vascular ultrasound examinations, demonstrating the skills and knowledge to assess technical data reflective of patient status relative to age and specific needs, and to assist in the interpretation of same, providing preliminary impressions as appropriate.
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Coordinate data infrastructure work to ensure appropriate tracking is in-place to conduct high-quality analyses. Experience working with cloud based data warehouses like Google BigQuery, Redshift, or Snowflake.
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The role of the RN Quality Specialist may include, direct patient/family care, consultation, change agent, teaching/coaching/mentoring, research, patient advocacy, performance improvement, and leadership & professional development.
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Very Good understanding in Data Foundation initiatives, like Data Modeling, Data Quality Management, Data Governance, Data Maturity Assessments and Data Strategy in support of the key business stakeholders.
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Managing ETL and data ingestion/storage pipelines via data warehouses, graph DBs, and vector databases (i.e. Snowflake, Amazon Neptune, Airflow) Building Retrieval Augmentation Generation (RAG) systems via chatbot interfaces for data retrieval and insight summarization.
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Part of this function involves ensuring as part of the data migration that data quality, integrity and completeness is maintained or improved and that duplicate entities are consolidated.
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Solid experience with architecting and implementing metadata management including data catalogues, data lineage, data quality and data observability for big data workflows.
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Experience with working in cloud-based data science, database, big data processing, and reporting tools – preferably on Azure such as Azure ML, Power BI, Azure Data Explorer/KQL, Synapse, Databricks, etc.
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data quality jobs Title: quality Company: Boeing in Atlanta, GA
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