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Job Description: GCP Data Engineer, Big data Technologies , Google Cloud Platform (GCP) data services such as DataProc, Dataflow, Cloud SQL, Big Query, Cloud Spanner in combination with third parties such as Spark, Apache Beam/ composer, DBT, Cloud Pub/Sub, Confluent Kafka, Cloud storage Cloud Functions & GitHub. Must have more than 6 years experience.
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Keywords: Golang, Web Application, Backend, Gin, Go kit, Java, Spring Boot, MySQL, PostgreSQL, MongoDB, Cassandra, CI/CD, Docker, Kubernetes, Communication, Collaboration, Teamwork, Learning, Growth, Agile (optional), Big Data (optional), Apache Spark (optional), Hadoop (optional), Google Cloud Platform (optional), Cloud Functions (optional), Cloud Run (optional), Cloud SQL (optional), Cloud-Native (optional.
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Experience in Data science, machine learning, or optimization models Experience in Python, Spark, Scala, or R, using open source frameworks (for example: scikit learn, TensorFlow, Pytorch) You are knowledgeable of databases, data warehouse design, cloud storage, and ETL best practices.
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Hands-on experience with “big data” technologies (e.g. Apache Spark, Google Dataproc, Google Big Query) and messaging technologies (e.g. Kafka, Message Queue (MQ), Java Message Service (JMS.
$85,000 - $120,750 a yearFull-timeExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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Master's or PhD degree in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field. Bachelor's degree in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, related field, or equivalent practical experience.
$142,000 - $211,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Google Big Query, AWS databases, Oracle SQL, mySQL, PostgreSQL, and other data technologies. Master Degree in Microbiology, Genomics, Bioinformatics, Computational Biology, Data Analytics, Data Engineering or life science and agricultural related quantitative disciplines.
$40.83 - $43.5 an hourExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience in the definition of Big Data architecture with different tools and environments: Cloud (AWS, Azure and GCP), Cloudera, No-sql databases (Cassandra, Mongo DB), ELK, Kafka, Snowflake, etc.
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Employ strong technical data science skills to build machine learning models to optimise digital customer journeys; pricing and promotions optimisation, recommenders and media campaign performance.
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Job Qualifications: How You Qualify Bachelor of Science (or higher) degree in Meteorology, Computer Science, or a related field, or at least 10 years of relevant experience in computer/systems administration, data operations, and related engineering.
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In this role you will have the opportunity to work with cutting edge cloud-native technologies including Google Cloud Platform (GCP), Spring Boot, React, Cloud SQL- Postgres, TypeScript, Dataflow and our enterprise dealership platforms.
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One of the goals of Digital Agriculture Program at Texas A&M AgriLife Research center at Corpus Christi is to develop and apply new and emerging technologies, including big data analytics, artificial intelligence (AI), remote data transfer, and cloud computing to help solve complex agricultural problems.
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Serve as a strategic leader as part of our data science & machine learning team, with responsibility for Xometry's pricing strategy. Build collaborative relationships with key stakeholders; set priorities aligned to business goals; communicate analysis, strategies, timelines, and work of the data science & machine learning team, and gain buy-in from executive leadership.
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Experience with SQL and cloud technologies like Snowflake, Google BigQuery, Databricks, presto etc., We need a strong data scientist leader to manage our ML & data science research & development and evolve the services that make up the backbone of Xometry’s business.
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The successful candidate will bring experience as a data scientist and machine learning leader working for a company where "AI" is considered core to the company's success. Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse.
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You probably have experience in designing and delivering solutions on Google Cloud, perhaps using serverless products such as App Engine and Firebase, or infrastructure such as Compute Engine and GKE. Ideally you will be qualified to Google Certified Cloud Architect, Data Engineer or Cloud Developer level, although good hands-on experience is just as valued.
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big data computer science google cloud jobs Title: machine learning engineer
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