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Kafka, Apache Pulsar, RabbitMQ, Amazon Kinesis, Apache Flume, Apache Storm, Apache Spark Streaming, Google Cloud Pub/Sub. OpenShift, Anthos, Google Kubernetes Engine (GKE), Azure Kubernetes Services (AKS), Amazon Elastic Kubernetes Service (EKS), Hashicorp Nomad.
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3+ years of experience with big data frameworks (Amazon EMR, Apache Spark) Work on public cloud infrastructure, Big data technologies, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Architect and develop large-scale, distributed data processing pipelines using technologies like Apache Spark, Apache Beam, and Apache Airflow for orchestration. Proven expertise in Apache Spark, Apache Beam, and Airflow, with a deep understanding of distributed computing and data processing frameworks.
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Big Data Technologies: Distributed Computing: Tools like Apache Spark, Hadoop. Software Engineering & DevOps: Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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Develop, program, and maintain applications using the Apache Spark open-source framework. Must be strong in Cloud AWS event-based architecture, Kubernetes, ELK (Elasticsearch, Logstash & Kibana.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL, Confluence, JIRA. Utilize programming languages such as Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
Part-timeExpandApply NowActive JobUpdated 27 days ago - UpvoteDownvoteShare Job
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Spark Developer must have strong programming skills in Java, Scala, or Python. Work with different aspects of the Spark ecosystem, including Spark SQL, DataFrames, Datasets, and streaming.
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Position:- Spark Tech Lead. NOTE:- Find Strong BigData resume with Strong Spark experience, Less Java experience will also work. Should have experience on Java, Python and Spark. Proven experience as a Spark Developer or a related role.
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Amazon Web Services (Security Groups, Batch, Lambda, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud.
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Your expertise in Apache Spark (Scala), Apache Airflow, AWS Glue, Python, Kubernetes, and Oracle will be crucial in ensuring efficient data processing, storage, and retrieval.
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Proficiency in Apache Spark open-source framework for application development. Expertise in Cloud AWS event-based architecture, Kubernetes, ELK (Elasticsearch, Logstash & Kibana.
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4+ years of experience with container & image management (AWS EKS, Kubernetes, Docker) Utilize programming languages like Java, Python, SQL, Node, Go, and Scala. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI.
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The tech stack is primarily AWS ECS with services written in Go, and DynamoDB as a back end datastore. Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.
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Spark Tech Lead. Strong experience in DevOps tool chain (Jenkins, Artifactory, Ansible/Chef/Puppet/Spinnaker, Maven/Gradle, Atlassian Tool suite) Good knowledge in technical concepts – Security, Transaction, Monitoring, Performance.
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Experience with Docker, Elasticsearch, Lucene, AWS cloud technologies, Apache Spark, Hadoop, and Hive. Experience with Ansible platform, including Kubernetes or AWS Elastic Container Services.
$81,800 - $186,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday
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