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Administration experience of distributed computation and streaming frameworks, like Kafka, Cassandra, Elasticsearch, Flink, Storm, Spark, and cloud services EMR, Dataproc, Elasticache, AWS RDS, GCP SQL or similar.
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Experienced with open source big data processing technologies such as Airflow, Hive, Flink, Spark, Kafka, Storm, etcKnowledgeable with Data Science tools and frameworks. Unified Care specialists support patients at home between doctor’s appointments with remote patient monitoring (RPM) and chronic care management (CCM) to achieve better health outcomes.
$140,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Familiarity with big data technologies such as Apache Spark, Hadoop, etc. The Commerce team provides the transactional engine for App Store, iTunes Music Store, Apple Music, iBook Store, Apple TV+ and more.
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Experience with databases and data solutions such as MongoDb, MariaDb, Microsoft SQL, Spark and Kafka. Automation, CI/CD and container using technologies such as Git, Kubernetes, Docker, Rancher, and Armada.
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Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)Primary Location.
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Minimum Qualifications- 5+ years of hands-on experience in developing, implementing, and validating Transaction Monitoring programs- Bachelor's degree or above in Computer Science/Statistics/Mathematics or other related majors- Proficient in data processing and analytics in big data environment using SQL/Hive/Spark etc- Mastery of at least one prevalent programming language for data science, such as Python, Java, or Scala.
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Sr. Data Engineer with Spark, Scala, Google Cloud Platform - Sunnyvale, CA (Hybrid) Role: Sr. Data Engineer with Spark, Scala, Google Cloud Platform (13145-1) Spark 8+ Yrs of Exp.
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You know data structures, you know Python and (optionaly) Go. Our tech stack Google Cloud Platform, DataFlow, Apache Beam, BigQuery, BigLake TableOpen formats IceBerg, Avro, ParquetDataProc, Spark, Flink, PrestoPython, GOApache Kafka, Kubernetes, GitLabBigTable, Mongo, Redis.
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Experience in building low-latency, high-availability data stores for use in real-time or near-real-time data processing with programming languages such as Python, Scala, Java, or JavaScript/TypeScript, as well as data retrieval using SQL and NoSQL.Hands-on expertise in data technologies with proficiency in technologies such as Spark, Airflow, Databricks, AWS services (SQS, Kinesis, etc.
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Experience with Machine Learning tools (Tensorflow, Apache Spark) Experience with Machine Learning tools (Tensorflow, Apache Spark) Demonstrated experience with popular software stacks e.g. Python-Django, Ruby on Rails, LAMP.
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Ability to work with a small team of engineers to build, implement and commercialize a data analysis platform that manages tools including Spark, Flink, Airflow and Superset. Experiences in big data tools such Spark, Dela Lake, Jupyterhub and analytics tools.
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Experience with Spark, preferably Databricks. Has experience with distributed compute preferably Spark. With our partners at John Deere, we have the ability to bring innovative computer vision, machine learning, robotics, and product management solutions to scale production, maximizing their potential impact.
$148,000 - $240,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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This is an opportunity to work on interesting data engineering anddata science problems, build large scale distributed machine learningsystems from the ground up, anduse cutting edge Big Data technologies like Spark, Kafka, HBase and Hive. RESPONSIBILITIES: ● Design and implement data pipelines empowering real timeinsights.
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Big Data Tools: Kubernetes (K8s), Hadoop, Spark, Postgres, Databricks, Azure cloud offerings including (Azure Synapse, ADLS, Azure Functions) Big Data Tools: Kubernetes (K8s), Hadoop, Spark, Postgres, Databricks, Azure cloud offerings including (Azure Synapse, ADLS, Azure Functions.
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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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spark job Title: assistant Company: Boys And Girls Club Of Bluffton in Santa Clara, CA
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