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We utilize a plethora of open source and industry accepted technologies for our big data problems such as Apache Spark, Apache Storm, Amazon Web services, and Apache Kafka. e Apache Spark or Apache Storm or Celery.
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Familiarity with graph querying tools such as Apache Tinkerpop Gremlin, Apache Spark Graphframes, or graph databases. New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning EngineerSan Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning EngineerRemote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning Engineer.
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Excellent knowledge of Python, Spark, and T-SQLHands-on experience on crafting and developing scripts for ETL processes and automation in Azure data factory, Azure Databricks and PySparkGood understanding of data modeling and ability to apply different techniques within a cloud platform.
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Experience in stream / data processing technologies like Kafka, Spark, Google BigQuery, Google Dataflow, HBaseFamiliarity designing CI/CD pipelines with Jenkins, Github Actions, or similar toolsExperience with SQL, particularly performance optimizationExperience with Graph and Vector database or processing frameworksStrong knowledge of data modeling, data warehousing, and data integration best practices.
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Understanding of foundations of Big Data systems and hands-on experience with distributed computational frameworks such as Apache Spark / Apache Beam and NoSQL data stores. Experience with working on large data sets, especially with Spark, Python and Java. Experience with cloud computing platforms, such as AWS or GCP. Experience with Kubernetes.
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Experience designing and implementing distributed systems using frameworks such as Apache Kafka, Apache Spark, or similar. Knowledge of simulation software and familiarity with industry-standard tools such as ANSYS, COMSOL, or similar.
$150,000 - $200,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise in data warehousing and ETLs (e.g. AWS Redshift, AWS Glue, Spark, AWS S3 or equivalent) Hands-on AWS services, Terraform IaC, Containerization, CI/CD experience. Experience using Redshift, AWS Glue, EC2, Lambda, RDS (PostgreS), S3, Dynamo.
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Deep understanding of cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Apache Spark, Kafka). Deep understanding of cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Apache Spark, Kafka.
$130,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Must be familiar with Data Science concepts including at least one of: Experience with Python Experience with data science programming in Python including numpy, pandas, scikit-learn, pytorch, matplotlib Experience with databases and SQL Ideally, experience with big data tech stacks such as map-reduce, spark, etc.
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Python or related language- Experience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
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Because diversity, equity, and inclusion are at the core of Brandeis’ history and mission, we value and are seeking candidates with a variety of social identities, including those that have been underrepresented in higher education, who possess skills that spark innovation, and who, through their scholarly pursuits, teaching, and/or service experiences, bring expertise in building, engaging and sustaining a pluralistic, unified, and just campus community.
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Experience in Excel, Stata, Python, R, SQL, SAS, ArcGIS/ArcPy, or Cloud computing (Databricks/Spark, Google Cloud, Azure, AWS); Experience in Excel, Stata, Python, R, SQL, SAS, ArcGIS/ArcPy, or Cloud computing (Databricks/Spark, Google Cloud, Azure, AWS.
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Experience with working on large datasets, especially with Spark. Conducts research in state-of-the-art deep learning models focused on EHR data, cardiac tools (ECG, imaging), and publish your novel findings.
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SCALA, SPARK, SQL, HADOOP, AWS, HIVE, Spark SQL, HIVE QL, CICD (Continuous Integration/Continuous Delivery), VCS (GIT HUB) Hands-on experience of SQL in Big Data: SQL, Spark SQL, Hive QL.
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Insightful experience with big data technologies like Hadoop, real-time processing frameworks (e.g., Apache Spark), and advanced knowledge of SQL and data architecture. Hands-on experience working with technologies like Spark for data processing, ETLs for data pipelines and queueing systems (Kafka, RabbitMQ.
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spark job in Somerville, MA
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