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1+ years’ experience in Big Data Distributed ecosystems (Hadoop, SPARK, Unity Catalog & Delta Lake) 1+ years’ experience in Big Data Distributed systems such as Databricks, AWS EMR, AWS Glue etc.
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Expert level in Designing and Architect solutions in Azure Data factory, Azure Databricks, Azure Datalake, Delta Lake and Azure synapse analytics implementation. · Experience in Azure cloud technologies like PySpark, Synapse, ADF, Databricks, Python, Scala and SQL. · Have good experience configuring Microservices using Docker, Kubernetes on Azure Data Bricks Extensive Experience on working on Azure AI services including Data Bricks and Azure cognitive services.
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Experience with Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Snowflake and/or equivalent cloud data technologies and platforms. Experience with data platforms supporting Data as a Product, Data as a Service, Data Mesh, Data Virtualization, Delta Lake, Lakehouse and/or Data Fabric.
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Data processing/data transformation using ETL/ELT tools such as DBT (Data Build Tool), or Databricks. Experience working with cloud data solutions (Delta Lake, Iceberg, Hudi, Snowflake, Redshift or equivalent.
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Experience with cloud computing (AWS, Microsoft Azure, Google Cloud) to help secure your financial future and preserve your health and well-being, including:Premier Medical, Dental and Vision Insurance with no waiting period.
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Good to have knowledge of Databricks Lakehouse, Delta Lake, Delta live Tables (DLT) Good to have knowledge of Databricks Lakehouse, Delta Lake, Delta live Tables (DLT) Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
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Pyspark, SQL, CI/CD Pipelines for Databricks, ETL Processes, Project Management, Delta Lake Storage. Role: Databricks Architect. Pyspark, SQL, CI/CD Pipelines for Databricks, ETL Processes, Project Management, Delta Lake Storage.
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Develop and manage data lakes using Delta Lake and various file formats leveraging Azure Gen2 Data Lake. - Implement event-driven architectures using Azure Service Bus, Azure Event Hubs and Azure Event Grid. - Design, implement, and maintain data pipelines and ETL processes using Azure Data Factory, Azure Databricks, and other Azure services.
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Experience with Data Engineering such as Databricks is required. Experience with understanding and developing data lake/delta lake eco systems is required. Experience with Data Engineering such as Databricks is required.
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15+ years’ of experience in a technical role with expertise in data governance and data warehousing - such as setting up DataBricks as a Service model. Deep Specialty Expertise with scaling big data workloads that are performant and cost-effective - including technologies such as Delta Lake.
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Databricks , Azure and Delta Lake. Implement scalable and sustainable data engineering solutions using tools such as Databricks, Azure, Apache Spark, and Python. Implement scalable and sustainable data engineering solutions using tools such as Databricks, Azure, Apache Spark, and Python.
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Experience Required: 7+ plus years of experience in solutioning data pipeline for large enterprise data Warehouse applications using Azure Data Factory, Data bricks, Data Ingestion, Data Transformation /Computation, Orchestration, Reporting & Data Analytics Knowledge of Azure Services such as ADF, Databricks, Event Hub, Delta Lake, Data Lake Strong command on Python, Pyspark , SQL & Power BI Experience in GitHub , Git Action , Jira end to end data pipeline.
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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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More than 10+ years of relevant experience in data engineering tools like Azure Data pipelines , Azure Data factory, Azure Data Lake Storage, Databricks, Demonstrated experience in building, tuning data pipelines on Spark, Cloud native tools like Azure Data Factory, Databricks and ETL tools.
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Deep understanding of Databricks architecture, including Delta Lake, Spark, and MLflow. Deep understanding of Databricks architecture, including Delta Lake, Spark, and MLflow. Proven expertise in designing and implementing data platforms on AWS, including EC2, S3, EMR, Redshift, and other relevant services.
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