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A strong DevOps, Data Engineering background with working knowledge of data processing, CI/CD, and analytics tools on AWS platform. Develops and maintains enterprise infrastructure by creating efficient, adoptable frameworks to be used across the organization for the data operations platforms in use like Databricks, EMR, AWS services, and 3rd party monitoring tools like Monte Carlo and Datadog.
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Document classification and extraction: Data scientists can use natural language processing (NLP) techniques to classify and extract information from documents, such as news articles and social media posts.
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High familiarity with data platforms and applications like Databricks, Jupyter, Snowflake, Airflow, FiveTran, DBT. Proficiency in SQL and experience with data visualization tools like Tableau, Looker, or similar.
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Identify and implement solutions to optimize data storage, retrieval, and processing. You have 8+ years of industry experience and proficiency in building distributed data pipelines for both batch and real-time (experience with Databricks, Spark, Hive, Iceberg, Kafka, Snowflake is helpful, but not strictly required.
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Minimum 2 years of management and leadership experience Knowledge of Windows workstation platforms, Azure AD, Intune/Modern Management, GPO, Microsoft o365, Microsoft Endpoint Configuration Manager (formerly SCCM) Limited immigration sponsorship may be available Preferred Technical skills: Data Science / Analytics using a multitude of data sources.
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Collaborates with technology and platform management partners to optimize data sourcing and processing rules to ensure appropriate data quality as well as process optimization. Manages data migrations/conversions and troubleshooting data processing issues.
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Lead maintenance, data entry, cleanup and accuracy of donor database for institutional funder records. Collaborate with program staff and Case Management and Data Specialist to collect program outcomes and other required information.
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Assist with the preparation of technical project documents, including, but not limited to: writing, word processing, building tables and spreadsheets, tabulating and manipulating data, producing hard copy documents, completing air and erosion control engineering calculations commensurate with the candidate's background.
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In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies. Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire.
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Extensive knowledge of coding in Python or Scala with a focus on data processing. Collaborate with Data Scientists and Business Intelligence Analysts to ensure efficient and effective data processing and analysis.
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Be a key part of our development team to define the new pipelines, optimizations, and standards for 3D geospatial data processing. Exposure to geospatial software and/or data such as photogrammetry, point clouds, and terrain, or other large 3D models.
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Bring your people analytics, social science research and data mining/science skills to a unique team seeking to understand, and shape, the future of the digital workplace. In addition to your existing people analytics work experience, this role will combine your skills in psychology, data analytics and visualisation, to help create a more effective workplace.
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High proficiency in using Excel and/or Google Sheets formulas and pivot tables to manipulate, compile and analyze data. Manage the Student Information Systems Analyst to maintain key student data and various educational technology systems that integrate with our student information system (including Mosaic, Clever, Illuminate, DeansList, etc.
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Expertise in two or more data estate workloads like Microsoft’s Data & AI Platform (Azure Synapse Analytics, Azure Databricks, CosmosDB, Azure SQL, HDInsight, etc.) As a Senior Sales Specialist - Data & AI you will be a senior solution sales leader within our enterprise sales organization working with our most important customers.
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Extensive knowledge of coding in SQL with a focus on data processing. Knowledge of, or experience with, healthcare data standards such as HL7, FHIR, ICD, SNOMED, LOINC. Comfortable working with unstructured and semi-structured data (Web scraping.
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