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Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Airflow, Redshift, Databricks, EMR. Experience with data warehouse platforms such as Redshift, Databricks, Big Query, Snowflake.
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Design, implement and support data lakehouse infrastructure using modern cloud-service stack (AWS preferred): Python, S3, Batch, Lambda, EKS, IAM, Rest (Redshift, Glue, Athena, ECR, Parquet is a plus.
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Experienced in building SaaS solutions with agile principles and a strong background in cloud infrastructure technologies (i.e. Microservices Architecture, RESTful APIs, AWS, Kubernetes, Kafka, RDS, NoSQL.
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Experience working with relational and NoSQL databases, as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage, Azure Blob Storage). Solid understanding of data engineering concepts, including data modeling, data processing pipelines, and big data technologies (e.g., Hadoop, Spark, Kafka.
Full-timeExpandApply NowActive JobUpdated 20 days ago - UpvoteDownvoteShare Job
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AWS Certified Big Data – Specialty or other relevant AWS certifications. Strong experience with big data technologies and frameworks such as Hadoop, Spark, Graph DB, or Kafka.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Experience with Cloud Services (AWS, Google Cloud, Microsoft Azure, etc.
$195,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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6+ years' experience in engineering data pipelines using big data technologies (Spark, Flink etc. Architect cloud-based data pipeline solutions to meet stakeholder needs.
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Amazon Web Services (AWS) offers a complete set of cloud services that enable all companies, from startups to enterprises, to run virtually everything in the cloud, including mobile applications, big data analytics, AI/ML platforms, and microservices/serverless infrastructures.
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Or Scala, and experience working with modern web frameworks like React, Angular, or Vue.js. Experience in developing and Maintains application on Palantir Foundry Platform. Participate in architectural discussions, technology evaluations, and solution design sessions to shape the long-term technical vision of Palantir's products.
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Role: Palantir Tech Lead. We believe in providing staffing solutions to address the current talent gap – Right Talent – Right Time – Right Place – Right Price and acting as a Career Coach to our consultants.
$150,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience with Big data technologies such as AWS EMR, Spark, Machine Learning (AWS SageMaker) and one or more cloud environments (AWS, Google and Azure) Experience with a modern Infrastructure as Code framework like Terraform, AWS Cloud Formation, AWS CDK, Pulumi, etc.
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Demonstrating relevant project management experience in organizing and leading teams including Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development (tools: IICS/AWS Glue/SAP BODS/ SSIS/SnapLogic); preferable in P&C Insurance data warehouse.
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The platform is based on micro-services (using Akka and Play Framework), Containers (using Docker/Kubernetes) and Big Data (using Hadoop/Spark). Experience in cloud engineering experience (Amazon AWS, Microsoft Azure) in deploying and managing production environments.
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Experience working in AWS cloud environment in designing and implementing a cloud data warehouse, other types of storage, and developing ETL/ELT pipelines. Step into Nas’ recording studio and Gordon Ramsay’s kitchen, and go behind the big screen with James Cameron.
$161,500 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.
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