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Design, develop, and implement robust and scalable data solutions utilizing Azure technologies, including Azure Data Factory, Azure SQL Data Warehouse, Azure Databricks, and/or Azure Synapse Analytics.
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Knowledge of Cloud Infrastructure and services including Azure Data Factory(ADF), Azure Synapse, Azure Synapse Pipeline, Spark Notebooks, Azure Synapse Dedicated SQL Pool Warehouse ,Azure Databricks, Azure Functions, Power BI and Azure Data Lake storage.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Hands on experience in Snaplogic, Databricks, ADLS, TWS, Spark, ETL, Sybase, Oracle. Voya is seeking a skilled and motivated technician with expertise in Azure Data Factory and Snaplogic data integration to join our dynamic IT team.
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Past experience in BigData development is preferable (Streaming on Apache Flink or Apache Spark) or else should be able to demonstrate conceptual differences between batch and streaming data processing.
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Hands-on experience with big data processing frameworks (Apache Spark, Apache Hadoop). Proven experience as a Data Engineer, Data Architect, or similar role with a focus on AWS technologies.
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Experience in one or more of the following languages: Python, SQL, Spark. Expertise in Statistical Programming Software such as R, and experience in data analysis. This role provides an opportunity to develop models for deployment on the Quantitative Finance Analytical Platform, a proprietary platform for advanced computational needs within Corporate Treasury.
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Although this is not a hands-on role, you should have worked extensively with technologies such as AWS, Python, Snowflake, Hadoop, Hive, Spark, HBase, and more. Provide thought leadership on High-Level Architecture and Design, data modeling, and Big Data strategy, both to peers and to key stakeholders in the Client.
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2+ years big data experience, including Hadoop, Hive, Spark. 3+ years in GCP BigQuery with DataFlow, Data Form, DataStudio, and Looker. Identify data sources and build pipelines using various ETL tools such as SSIS and Alteryx.
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Experience in predictive modeling, data science, and analysis in both batch and streaming settings. Proficiency in Python/R, Hadoop, Spark, MySQL with documentation for reproducibility.
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Experience with big data technologies such as Hadoop, Spark, or cloud-based platforms like AWS, Google Cloud, or Azure. You understand the data science lifecycle and are experienced in development and implementation of advanced statistical models and machine learning algorithms.
$148,960 - $238,560Full-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Familiarity with big data tools and frameworks (e.g., Hadoop, Spark) is a plus. Design and implement highly scalable, high-volume data pipelines and warehouses using Azure Data Factory, Azure Databricks, and other Azure services.
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Solid understanding of Hadoop ecosystem components, including HDFS, MapReduce, Hive, Kafka, Spark, Docker, etc. As a Hadoop Platform Tester, you will play a crucial role in ensuring the quality and reliability of our cyber security platforms leveraging Hadoop technologies in our Incident Response Team. This includes Data Quality, Integration, Regression and Security Testing.
$128,400 - $215,800 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Skills and Experience: Required: 6 years of overall IT experience 3 years of experience with high-velocity high-volume stream processing: Apache Kafka and Spark Streaming Experience with real-time data processing and streaming techniques using Spark structured streaming and Kafka Deep knowledge of troubleshooting and tuning Spark applications 3 years of experience with data ingestion from Message Queues (Tibco, IBM, etc.
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Built high throughput real-time and batch data processing pipelines using Spark, Kafka, on AWS environment with AWS services like S3, Kinesis, Lamdba, RDS, DynamoDB or Redshift. Experience with big data technologies and exposure to Hadoop, Spark, AWS Glue, AWS EMR etc.
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Hadoop MapReduce, Cascading/Scalding, Apache Spark, AWS EMR. Spark streaming, Kafka, Apache Storm, Flink NoSQL. Hadoop MapReduce, Cascading/Scalding, Apache Spark, AWS EMR. Database/Search – Oracle, complex SQL queries, stored procedures, performance tuning concepts, SOLR, AWS RDS, AWS Aurora.
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