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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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Additional duties are to provide system administration tasks for all DCIM systems which are comprised of EPMS’s, BMS’s (Building Automation Systems) and SCADA (Supervisory Control and Data Acquisition Systems.
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. Job Responsibilities:- 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.
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Strong technical proficiency to contribute to data engineering task in an AWS and Databricks ecosystem. You must be passionate about data management with a solid background in AWS, Databricks, Python, Trino/Starburst, Databases and SQL.Design, develop, monitor, and maintain data pipelines in an AWS Gov Cloud ecosystem with AWS, Databricks, Delta Lake and Trino as the underlying platforms.
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4+ years of professional experience as a data scientist in the SaaS industryWorking knowledge of Unix command-line/shell and gitExperience deploying models in a production environment, ideally with Databricks.
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Prior to Nutanix, I founded a VC-funded start-up in AIOPs space and did a PhD in the area of data center operations management from Georgia Tech. I hold a B.Tech. from IIT Kharagpur. Expert in Python especially in AI/ML libraries such as PyTorch, Tensorflow, Sklearn, LLM tools such as Spacy, and data engineering tools such as Pandas, Numpy, Spark.
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Snowflake Management: Manage Snowflake data warehouse environments, including provisioning, configuration, optimization, and monitoring. Develop ETL processes to extract, transform, and load data from various sources into the data warehouse.
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Experience with data warehouse design, implementation, and optimization. Data Processing: Develop and implement data processing pipelines using Apache Beam, Apache Spark, or other suitable frameworks to transform and cleanse data for analysis.
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake,Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). 3+ years' of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M.
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With capabilities spanning technology, data science, supply chain management, fulfillment, customer service, and more, we help brands launch, scale and grow—across product categories and geographically.
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Design and implement automated solutions for data normalization and taxonomy management using tools such as Python, R, SQL, and automation platforms. Gen3 is currently seeking a talented Data Scientist to join our team, dedicated to supporting the Internal Revenue Service (IRS) on the ISSM Vulnerability Compliance and Remediation Program.
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The candidate should have expertise in data modeling, SQL, Python, R, data warehousing, big data technologies, data pipeline construction, data quality, cleansing, version control, cloud services, machine learning, feature engineering, deep learning, and natural language processing.
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In this role, you will construct data analytical infrastructure, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis. Axient is seeking a Mid-Level Data Engineer to join our analytics team in Huntsville Alabama.
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Leverage cloud platforms (e.g., AWS, Azure, Google Cloud/BQ, Databricks) for scalable and efficient data processing and storage. Data Pipeline Construction - Develop and maintain end-to-end data pipelines for streamlined data processing and analysis.
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As the Data Scientist, you will use Google Cloud Platform (GCP) tools and technologies, such as Vertex AI and BigQuery, to build, deploy, and monitor scalable and robust machine learning solutions.
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data job Title: warehouse Company: Amerisourcebergen
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