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Kinesis/Firehose, Airflow, Glue,Spark, EC2, SageMaker, S3, NoSQL database and API Gateway. Expertise architecting and developing solutions in AWS, Databricks and Snowflake (data engineering) Senior Architect Data Engineering - Snowflake and Databricks page is loaded.
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Experience with data warehouse and big data technologies such as Azure Synapse Analytics, Azure Data Lake Storage, Spark, Kafka, Databricks, and Containers. Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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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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Familiarity with big data processing tools (e.g., Hadoop, Spark) is advantageous. As a Junior Machine Learning Engineer, you will have the opportunity to work on exciting projects, develop your skills, and contribute to the development and implementation of machine learning solutions.
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Must have 6 + years of experience on using AWS Native Data Services Must have expertise in the following:- AWS Native tools : Lambda, Glue, Spark,Aurora and Snowflake. Primary - AWS DBT, Glue, Spark, Lamda, S3, EC2.
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Perform complex application implementations using latest techniques and technologies such as AWS, Hadoop, Apache Spark, Python, SQL, etc. Hadoop, Hive, Pig, Impala, Oozie, MapReduce, Apache Spark etc.
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Candidate should have experience/knowledge of the following: HPC job scheduling systems such as LSF, SLURM or Apache Spark, automation and orchestration frameworks like Ansible, Puppet and Chef, strong bash scripting skills.
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Extensive experience with Apache Spark for distributed data processing. Design and develop identity graph-based solutions leveraging technologies such as Python, Scala, Spark, and SQL.
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2+ years’ experience in NoSQL databases and close familiarity with technologies/languages such as Python/R, Scala, Java, Hive, Spark, Kafka. 2+ years’ experience in NoSQL databases and close familiarity with technologies/languages such as Python/R, Scala, Java, Hive, Spark, Kafka.
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