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Expertise in big data technologies (e.g., Hadoop, Spark, Kafka, and cloud platforms like AWS, Azure, and GCP). Automate data processing tasks and workflows using scripting languages (e.g., Python) and orchestration tools (e.g., Airflow.
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Demonstrating relevant project management experience in organizing and leading teams including Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development (tools: IICS/AWS Glue/SAP BODS/ SSIS/SnapLogic); preferable in P&C Insurance data warehouse.
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MS Office proficiency with Advanced Excel skills required Experience working with big data files, with the ability to summarize for a meaningful business discussion is a plus. 3 to 5 years' experience in Price / Cost / data processing analysis preferred Prior experience in manufacturing or distribution preferred.
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Experience on big data technologies and tools (e.g., Hadoop, Spark). Experience with database management and data processing. At least 2 from the following: Statistics and Probability Theory, Regression Modelling, Clustering Methods, Deep Learning, Neural Networks, Natural Language Processing, Text Mining, Computer Vision, Image Recognition, Time Series Forecasting, Machine Learning Visualization Tools, Tree Ensembles.
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Our transportation client is looking for a Big Data Engineer - Spark/Databricks to join their team. Experience with real-time data processing and streaming techniques using Spark structured streaming and Kafka.
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Experience with big data processing frameworks such as Apache Spark, Apache Hive, Apache Flink, and Apache Kafka. - Design, implement, and manage ETL pipelines for big data processing in Hadoop and Azure environments.
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Intercontinental Exchange (NYSE:ICE) is seeking a Senior Java Developer with a strong interest in analyzing and visualizing large datasets using big data technologies such as Kafka and stream processing.
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MS in Computer Science, Information systems, or Computer engineering, Systems Engineering with relevant experience in Text Mining / Natural Language Processing (NLP) tools, Data sciences, Big Data and algorithms.
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Applying knowledge and work experience in Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL/ELT pipeline development (tools: IICS/AWS Glue/SAP BODS/Matillion/DBT/Abinitio/SSIS/SnapLogic); preferable in P&C/L&A Insurance data warehouse.
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As part of this team, you will accelerate several architectural efforts - achieve orders of magnitude data processing latency improvement, creating comprehensive patient health records that can scale to entire populations of nations, creating a health data lake at massive scale to enable a host of intelligent health services.
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Utilize Databricks for big data processing and streaming analytics. Leverage AWS cloud services like S3, Redshift, EMR, Glue, Lambda, and others in combination with Data Lakehouse platform/Apache Spark Integration for advanced data processing and analytics.
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Hands-on experience with high-velocity high-volume stream processing: Apache Kafka and Spark Streaming. The candidate will participate in all phases of the Data Engineering life cycle and will independently and collaboratively write project requirements, architect solutions, and perform data ingestion development and support duties.
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Experience with big data technologies (e.g. Apache Spark, Hadoop) and data processing frameworks. Integrate data platform infrastructure with other systems fostering seamless collaboration among teams e.g. system integration with Fivetran, Monte Carlo, Salesforce Data Cloud, Tableau, Looker, Teradata, Bigquery.
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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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The Scientists help push the envelope of what is possible in the big data space; streaming live data into a data lake and experimenting with data in the data sandbox.
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big data processing jobs in Atlanta, NY, Germany
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