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4+ Experience with technologies Apache Mesos, Marathon, or Apache Spark. We are seeking DevOps Engineers who are passionate about marrying data with emerging technologies to join our team.
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Experience in Cloud and Big Data platforms such as AWS, Databricks, Snowflake, Hive, Pig, Apache Spark, etc. As a Data Scientist AI/ML Engineer within Asset and Wealth Management, you will be collaborating closely with various teams to prototype, build, test and deploy a large scale federated LLM platform.
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Implementation of Apache camel Routes, dealing with REST API, SOAP API, Talend Bigdata components like Spark, Hive, Sqoop, String Kafka etc. Experienced in using Talend Data Fabric tools including Talend DI, Talend Bigdata, Talend MDM, Talend Data Quality, Data Governance, and Talend Data preparation, Enterprise services Bus, Talend Cloud, TAC and TMC.
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Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow, and similar related technologies. Experience with analyzing large data sets using Hadoop, Spark, or related technologies is a plus.
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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.
$216,800Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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I worked extensively on POCs, Consulting Solutions, ETL Framework/ Architecture, Big Data technologies, Talend Master Data management, Performance optimization, ETL techniques, pilot projects, SQL Views etc.
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Active Google Cloud Data Engineer Certification Hands on in designing, building and operationalizing large-scale enterprise data solutions and applications using one or more of GCP data and analytics services in combination with 3rd parties - Python, Pyspark, Spark, Hive, Cloud DataProc, Cloud Dataflow, Apache Beam/ composer, Big Table, Cloud BigQuery, Cloud PubSub, Cloud storage Cloud Functions & Github.
$123,000 a yearFull-timeExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Ideally you have an in-depth understanding of streaming data technologies like Amazon Kinesis or Apache Kafka, and experience with open-source data processing frameworks like Apache Spark, Apache Flink, or Apache Storm.
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O Programming Language: Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting. Use programming languages including but not limited to Python, R, SQL, Java, Scala, Pyspark/Apache Spark, Shell scripting.
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ML | AI | Machine Learning | DevOps | Data & Analytics | Infrastructure | CI/CD | Terraform | Gitlab | Azure Devops | AWS | Azure | DataBricks | Ansible | Apache Spark | Kafka | Kubernetes | Docker | Linux.
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Leverage AWS cloud services like S3, Kinesis, Redshift, EMR, Glue, Lambda, and others, in combination with Data Lakehouse platform/Apache Spark Integration for advanced data processing and analytics.
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A critical part of realizing this vision is the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance, yet retain the expressiveness and of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science.
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Hands-on experience with the Databricks platform and Apache Spark. Proficient in programming languages such as Python, Scala, or SQL. In-depth knowledge of Apache Spark and its ecosystem.
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Experience in Installing, Configuring, tuning, and monitoring Apache Spark and Airflow on Kubernetes. Strong knowledge of Apache Spark and Apache Airflow architecture.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Experience with Apache Airflow, Hive, Snowflake, Kafka, Python.
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apache spark jobs Title: data scientist decision in Phenix-city, Alabama
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