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At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) As a Capital One Lead Data Engineer, you'll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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Experience with Terraform, Docker, Kubernetess, AWS/ECS (Azure, Google Cloud) Deployments, Jenkins or other CI/CD tools is a plus. As a Senior Software Engineer at GoHealth, you will play a key role in the development and enhancement of our Customer 360 platform and Delta Tables datalake in Databricks.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Working experience with cloud infrastructure (Google Cloud Platform, AWS, Azure, etc). Extensive experience implementing Data Warehouse (Star / Snow flake schemas) using SQL Server or equivalent, Big Data – HDFS, Elastic Search, ETL process development using IBM Infosphere or equivalent, Reusable Frameworks.
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Experience with ETL job schedulers (Apache Airflow, Azure Data Factory, etc.) Integration of factory data into on-premise and cloud-based Azure IoT tools to support the reliable, consistent consumption of real time data.
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4+ years of Azure Tooling experience for Cloud Migration and developing Data Warehouse. An ideal candidate has strong expereince in Data Engineering, Azure technologies, insurance industry background.
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Implementation expertise in Azure data analytics technologies including Azure Data Factory, Azure Data Lake, Azure Databricks. This individual in Senior Data Engineer role is responsible for tool and service designs within a technical domain that enable business strategies in accordance with architectural governance, standards, and policies.
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As a Lead Data Engineer at Disney, you will provide leadership and expertise in data engineering, fostering collaboration and best practices within the team. Experience with other cloud providers such as Azure or Google Cloud.
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Familiarity with cloud architecture in AWS, GCP, or Azure. Experience building applications using a Lambda or Azure function. Create CI/CD pipelines from data sources to data warehouse/data lakes.
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Very good knowledge in SQL (7+ out of 10) Databricks on Azure (7+ out of 10) PySpark (7+ out of 10) SparkSQL (7+ out of 10) Azure/ADLS (7+ out of 10) Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
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You have hands-on experience with cloud infrastructure and services, preferably Azure, as it relates to data integration/migration. Oracle Exadata / Snowflake / Azure / Airflow / Python / Kafka / Shell scripting / PowerBI.
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Cloud Platforms: Knowledge of cloud infrastructure and services, preferably Azure, as it relates to Snowflake and Databricks integration. The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities.
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In-depth understanding of data warehousing concepts, cloud platforms (AWS, Azure, GCP), and data modeling techniques. Creating new data pipelines, data transfers, and infrastructure to facilitate seamless data utilization within cloud environments (primarily Microsoft Azure.
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Knowledge of Azure Services such as ADF, Databricks, Event Hub,Delta Lake, Data Lake. 7+ plus years of experience in solutioning data pipeline for largeenterprise data Warehouse applications using Azure Data Factory, Databricks, Data Ingestion, Data Transformation /Computation, Orchestration,Reporting & Data Analytics.
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Understanding of cloud technologies such as Azure (preferable), google, AWS and snowflake. Hands-on experience with on-boarding metadata from various sources including SQL Server, Oracle, Azure cloud and others.
ExpandApply NowActive JobUpdated 2 days ago
azure job Title: data engineer in Chicago, Moapa, Nevada
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