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Other Tools and connectors - Ops/Cloud Manager, Compass, Connector for BI, Connector for Spark. Other Tools and connectors - Ops/Cloud Manager, Compass, Connector for BI, Connector for Spark. As a Technical Expert in all-things-search , you will be advising MongoDB field teams on Atlas Search and Vector Search issues, and helping with technical enablement in those areas.
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Hands-on experience with any of the following technologies: Spark; Istio/service mesh architecture; cloud security; Terraform/CloudFormation. Our vibrant and talented employees — or athenistas, as we call ourselves — spark the innovation and passion needed to accomplish our goal.
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Experience in multiple tools/language/frameworks within the Big Data & cloud ecosystem (Hadoop, MongoDB, Neo4j, Spark, Hive, HBase, Cassandra, etc. Designing, architecting, and developing solutions leveraging big data technology (Hadoop, Cassandra, Spark, Neo4j) to ingest, process, and analyze large, disparate data sets to exceed business requirements.
$259,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Our stack includes tools like Kubernetes, Jupyter, MLFLow, Airflow, Ray and Spark and we assist in deploying models touching nearly every part of Klaviyo’s business and product. Nice to have: Experience with large-scale data processing tools like Spark, Flink, Hive, Beam.
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Working with Teradata, Hive, Spark, Tableau, Postgres, other big data systems with Verizon grid computing infrastructure. Experience with Machine Learning, Statistics and Probability, NLP, Deep Learning especially experience in recommendation systems, conversational systems, information retrieval, computer vision, regression modeling.
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Experience in one or more languages like Java, R, MATLAB, Python - generators, iterators, comprehensions, Numpy, Pandas, Matplotlib, Sklearn, Keras, Tensorflow, Pytorch. Exploring research in the data science field and utilizing open source research results for the improvement of customer facing products.
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Develop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
$120,000 a yearFull-timeExpandApply NowActive JobUpdated 21 days ago - UpvoteDownvoteShare Job
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Extracts data using a variety of a programming languages, such as SQL, SAS, Python, or Spark/Scala, and applies knowledge of relational and non-relational database systems housed on both on-premise and off-premise (hybrid) platforms.
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Big data technologies like Hadoop (Hortwonworks, Cloudera, Azure HDInsight, Amazon EMR), Spark, Kafka, Elasticsearch and others; Big data technologies like Hadoop (Hortwonworks, Cloudera, Azure HDInsight, Amazon EMR), Spark, Kafka, Elasticsearch and others.
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Experience with Data Storage, Ingestion, and Transformation (Spark, Kafka or similar tools). With top adopters such as Lyft, Cisco, and eBay - not only do our products work at lightning speed, so do we.
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Applying knowledge and relevant work experience in Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development tools (tools: IICS/AWS Glue/Matillion/Abinitio SSIS/SnapLogic); preferable in P&C/L&A Insurance data warehouse.
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Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and/or experience with semantic search and retrieval frameworks (e.g., development and benchmarking of embedding models and retrieval approaches in the context of Retrieval Augmented Generation, RAG.
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
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In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. In-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc.
$276,100 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago
spark job in Waltham, MA
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