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Hands-on experience working with technology like queueing systems (Kafka, RabbitMQ, ActiveMQ, MSMQ), Spark, Hadoop, NoSQL (Cassandra, MongoDB), Play framework, Akka library. In order to accomplish this, we use state-of-the-art languages like Scala and Go, data technologies like Kafka and Spark, and agile development practices.
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Big Data(Spark, Scala) SQL - Hive, Teradata, Spark SQL. To discuss this amazing opportunity, reach out to our Talent Acquisition Specialist Rohan Salve at email address. Please Contact : To discuss this amazing opportunity, reach out to our Talent Acquisition Specialist Rohan Salve at email address.
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Strong data analysis skills (e.g., SQL, python, R) along with an understanding of technical patterns used to consume and process data at scale (e.g., graphQL, spark) You are also able to coach others and be a mentor in Ontology and Data Modeling.
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Utilize programming languages like Python, SQL, Spark, and Scala, Open Source RDBMS and NoSQL databases, AWS Fargate, and GLUE. Utilize programming languages like Python, SQL, Spark, and Scala, Open Source RDBMS and NoSQL databases, AWS Fargate, and GLUE.
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Proficient in project software: SAS/SQL, Databricks, Python, Spark languages/technologies Excel, Word, PowerPoint, Business Objects, and Outlook. Use SAS/SQL, Databricks, Python, Spark; other software as appropriate to task.
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3+ years of production experience with Apache Spark. 2+ years of experience with presentation and data analysis software such as: SAS, R, SPSS, MATLAB, QlikView, Excel and Access. Are you an experienced, passionate pioneer in technology - a solutions builder, a roll-up-your-sleeves technologist who wants a daily collaborative environment, think-tank feel and share new ideas with your colleagues - without the extensive demands of travel.
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Experience with big data technologies such as Spark, Kafka, or similar. The Tech Lead - Data & Customer Interface will report directly to the VP of Operations. Utilize expertise in reporting tools such as Power BI, Tableau, and Salesforce to create insightful and actionable reports for stakeholders.
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Hands-on coding experience in python/Scala, Spark, and visualization tool languages like Looker LookML. Leads the data operations needs for the Insights & Analytics team, providing technical direction and guidance in Spark, Python, AWS Cloud Technologies to address a wide range of advertisement and media related use cases.
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My client a top place to work in Philadelphia just called and needs to hire asap a great Data Engineer with SQL / Python / ETL with Databricks or Spark Azure Data Factory or AWS Glue. This is a contract to perm role.
$115,000 - $140,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Tech stack: React / C# / Azure / Apache Spark / Delta Lake / Unity Catalog / Databricks. Tech stack: React / C# / Azure / Apache Spark / Delta Lake / Unity Catalog / Databricks. These include, but are not limited to 1) the establishing of a Production environment in Databricks, 2) the orchestration of Unity Catalog for future state and scalability of data, 3) contextualized MLops/MLflow expertise and implementation, 4) additional silver and gold layer transformations relevant to business needs for data science, BI tools, Web App integration, etc.
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Experience with Glue, EMR, or Spark. Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office - whatever makes you the happiest and most productive.
Work from homeExpandUpdated 2 days ago - UpvoteDownvoteShare Job
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Proficiency in programming languages such as Python, Java, or Scala, and experience with stream processing frameworks such as Apache Kafka, Apache Flink, or Apache Spark Streaming. Stream Processing: Implement stream processing applications using technologies such as Apache Kafka, Apache Flink, Apache Spark Streaming, or AWS Kinesis to process and analyze real-time data streams.
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Configure and maintain systems including but not limited to Kubernetes (EKS and ArgoCD), Kafka, Spark, ElasticSearch/OpenSearch. Your expertise in Python, SageMaker, Spark, CI tools, SQL, Kafka, Kubernetes, and ArgoCD will be the driving force behind setting up fully automated CI/CD pipelines, solving operational challenges, and ensuring the optimal performance of complex systems.
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Knowledge of big data technologies such as Apache Spark. Experience with Databricks for data engineering and analytics preferred. Knowledge of big data technologies such as Apache Spark. Familiarity with data visualization tools (e.g., Tableau, Power BI.
RemoteExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
Part-timeExpandApply NowActive JobUpdated 6 days ago
spark job in Philadelphia, PA
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