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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
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Enable/Support platform to do distributed data processing using Apache Spark and other distributed / scale technologies. Kubernetes, Azure, Python, Data Science/ML. Deploy Application in Azure Kubernetes Service using GitLab CICD, Jenkins, Docker, Kubectl, Helm, Terraform and Manifest.
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Some of the technologies you’ll be working with include Apache Spark, Python, Terraform, Kafka, Azure EventHub, Vector DBs. You are well versed with infrastructure tooling such as Terraform, worked with Kubernetes, and have the SRE skill sets.
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Knowledge of distributed computing technologies such as Apache Spark, Hadoop, or Dask, and experience with containerization and orchestration technologies such as Docker and Kubernetes.
$150,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Docker/Containers/Kubernetes => 6/10 experience. Good understanding of distributed system like Spark and Kafka - Good to Have => 5/10. Build/Deploy AI/ML platform in Azure with open-source applications (Argo, Seldon) and/or cloud/SaaS solutions (Azure ML, Databricks, Truera.
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Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark. Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (Jenkins, Docker, Kubernetes, and Terraform.
$122,500 - $162,000 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Familiarity with data science platforms and software (e.g. Jupyter Notebooks, BinderHub, Apache Spark, Data Version Control, Delta Lake, Kubernetes, Kepler.gl) Familiarity with data science platforms and software (e.g. Jupyter Notebooks, BinderHub, Apache Spark, Data Version Control, Delta Lake, Kubernetes, Kepler.gl.
$97,000 - $135,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Familiarity with big data frameworks such as Apache Spark, Beam and Ray. Familiarity with cloud technologies such as AWS or GCP and using cluster frameworks such as Kubernetes or Mesos.
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Our technology stack runs on AWS, Kubernetes, Spark and Apache Airflow. Our technology stack runs on AWS, Kubernetes, Spark and Apache Airflow. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers.
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Experience working on internals of large-scale distributed systems and databases such as Apache Druid, Hadoop, Spark, Presto, ElasticSearch. Experience with Containers and orchestration services like Kubernetes, Docker etc.
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Hands-on experience with cloud computing using AWS, GCP or Azure. Utilize your expertise in Python, Golang, AWS, and SQL to deliver robust and scalable solutions. We are looking for an engineer with proven expertise in system architecture, microservices, and big-data processing and experience in building scalable solutions in the cloud environments.
$132,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes, or Terraform.
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Familiarity with big data tools like Apache Spark and their integration into ML workflows. Integrate DevOps best practices into the ML lifecycle to streamline deployment, scaling, and management using tools like Docker and Kubernetes.
$140,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Strong understanding and experience with distributed systems like Apache Spark, Ray etc. Strong experience with distributed systems like Apache Spark, Ray etc. Proficiency in containerization technologies like Docker and orchestration platforms like Kubernetes.
$200,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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SedonaDB and Apache Spark are built in Java and Scala, with deeply optimized Python wrappers and SDKs, and are deployed on cloud-based Kubernetes environments. Make open-source contributions to Apache Sedona, Apache Spark, and other open-source software packages where necessary.
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