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5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg.
$419,750 a yearFull-timeExpandApply NowActive JobUpdated 6+ months ago - UpvoteDownvoteShare Job
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Leverage AWS cloud services like S3, Kinesis, 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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Automate data workflows with ETL tools and frameworks (e.g., Apache Airflow, Talend) for efficient data integration and timely availability. Design and implement scalable, reliable data pipelines using technologies like Apache Spark, Hadoop, and Kafka.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Architect and Design: Design and implement scalable data solutions using AWS services (e.g., AWS EMR, AWS Athena, AWS Dynamo DB, AWS Glue, AWS S3) and Big Data technologies (e.g., Hadoop, Spark, Presto.
$202,276 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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AWS Data Engineer, Cloud Data Integration, Data Lakes, Data Pipelines, Data Modeling, AWS Data Ecosystem, Apache Spark, Scala, Python, Snowflake, SQL Programming.
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Design and develop production ready software using web, cloud and distributed technologies including Apache Spark, Hadoop, Microservices, and CI/CD cloud deployment. Analyze and design data models, data ingestion algorithms and performing data mining to identify patterns for fraud investigation, surveillance, and compliance on structured data sources, including Oracle and Big data solutions.
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Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure/AWS/GCP). As a data scientist for PRS, you will develop predictive modeling / machine learning solutions to complex business problems and create value to the business.
$172,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Experience in developing data pipelines using Apache Spark (Big Data Processing). Responsible for developing data pipelines using Apache Spark (Big Data Processing.
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The ideal candidate will have hands-on experience in migrating from Hadoop to Databricks and SQL to Databricks, with deep expertise in Apache Spark. In-depth knowledge of Apache Spark and the Databricks platform.
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DataBricks Architect with Apache, Spark, Python, ETL. Hands-on experience with Databricks platform and Apache Spark. In-depth knowledge of Apache Spark and its ecosystem.
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Design scalable patterns and architecture to support both batch and real-time data products & platform using big data technologies such as Hadoop, SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies.
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Youll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our T3 Fleet that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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You will also be building advanced analytics solutions while leveraging various cloud technologies in partnership with the Tech Product Team and Data Scientists to robustly scale up AI/Machine Learning models.
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AI Model Optimization: Work closely with data scientists and machine learning engineers to optimize NLP models, dialog management, and virtual agents. Proficiency in NLP: Strong knowledge of natural language processing (NLP) and machine learning concepts, with experience building and training virtual agents.
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machine learning big data apache spark integration jobs Title: data engineer
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