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Extensive hands-on experience with Microsoft Azure data services, including Azure SQL Database, Azure Data Lake, Azure Synapse Analytics, etc.
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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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Provide technical expertise and guidance on the selection, and hands-on implementation, and optimization of big data platforms, tools, and technologies across multiple cloud environments (e.g., AWS, Azure, GCP, Snowflake, etc.
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Deep knowledge & understanding of Azure technology stack: Azure Data Factory, Databricks, Synapse SQL Architecture, Azure DevOps. Strong Hands on Azure ADF , Databricks , LogAnalytic , DevOps.
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These are difficult hands-on engineering challenges that integrate biophysics, image processing, deep learning, novel electronics, ultrasound, and real-time signal processing that can only be solved with a tight-knit multidisciplinary team.
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We are working on challenging projects, migrating ETL jobs from Talend to DataBricks, building workflow automation solutions using Microsoft Power Platform, data flows with Azure data lake storage and DevOps environment set up.
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Hands-on experience using Snowflake DBMS Services (Snowsight, SnowSQL, SnowCD, REST API, Snowpark) and Microsoft Azure Cloud infrastructure and services (Azure Data Factory, DevOps, Data Lake Storage, Databricks, Purview, Kubernetes, Maps, etc.
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Hands-on experience with cloud platforms ( e.g., AWS, Azure, GCP ) and containerization technologies ( e.g., Docker, Kubernetes ), code management tools and frameworks ( e.g., Ci/CD, Git ) for understanding and managing big data solutions.
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Deep technical skills and experience with three or more of the following Microsoft technologies: Microsoft 365 Defender, AAD IPC, MDO, MDE, MDCA, MDI, Microsoft Sentinel, Entra , Azure AD , RBAC, Conditional Access, AzIP , Azure AD Connect, Azure MFA, Enterprise Permissions Management, Microsoft Defender for Cloud, Intune.
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Hands-on experience with Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure SQL Database, etc. 7+ years of experience as a Data Engineer, with a focus on designing and implementing data solutions on the Azure Databricks.
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1+ year of experience in data engineering using open-source technology stack along with cloud computing (AWS, Microsoft Azure, Google Cloud) Data Engineering experience focused on batch and streaming data pipelines development, Data processing/data transformation using ETL tools.
$72,000 - $185,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Overview Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs.
$130,000 - $170,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Using tools such as SQL, DataBricks, Talend, Python, Microsoft Power Platform and Azure Data Factory. Cloud Computing – Use the full range of Microsoft Azure Services with exposure to machine learning.
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The Enterprise OneStream RunTime team in the Enterprise Data and Machine Learning (EDML) organization supports the AWS hosted Data Ingestion and Data Processing applications enabling a centralized data movement platform across Capital One. You will get an opportunity and exposure to all possible data pattern combinations across Capital One and dive deep into the unique engineering challenges it brings around data integrity, security and scale.
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Hands-on experience in handling, processing, integrating, and analyzing large heterogenous biological data sets related to industrial drug discovery research (e.g., sc/snRNAseq, ATAC-seq, genomics, proteomics, etc.
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