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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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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. Thousands of organizations worldwide - including Comcast, Condé Nast, Nationwide and H&M - rely on Databricks' open and unified platform for data engineering, machine learning and analytics.
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Sr. SRE ( Site Reliability Engineer) - Data DevOps/ DataOps/ No- SQL, Kafka , Databricks, Kubernetes, Kafka , Terrafoam. Databricks Notebooks – There are a lot of jobs on Databricks – experience with Databricks to know how a notebook is created and run - run queries against the database and finding discrepancies and perform fixes.
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Build scalable data pipelines using varieties of tools, including Qlik Replicate, Five Tran, Databricks, etc. Demonstrated experience with Databricks, Microsoft Azure. Working knowledge of Azure Databricks.
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Minimum of 5 years of experience in data engineering, specifically with extensive use of Power BI and DataBricks. The successful candidate will be responsible for managing the Power BI platform, advancing data modeling in DataBricks, and leading a team of data engineers and visualization developers.
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Technologies like Azure Data Factory (ADF), Databricks, Delta Tables & Synapse will be used as the team oversees Eclipse data transformation & ongoing future development. Senior Data Engineer - Azure, Databricks, Python, Synapse, Azure Data Factory, Eclipse.
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Experience with data modeling, ETL/ELT development, data integration and orchestration techniques Experience with designing and developing end-to-end data and analytics solutions leveraging Azure Data Lake, Azure Databricks, and Data Factory Nice to Have: Experience with designing scalable data analytics architecture to implement advanced analytics solutions, including machine learning and AI, to extract actionable insights from data.
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Qualifications and Skills IT professional experience in Azure Cloud with over 5+ years of Azure Development Ability to recreate existing legacy application logic and functionality into Azure Databricks/Data Lake, SQL Database and SQL Datawarehouse environment.
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Experience with Databricks for data engineering and analytics, including familiarity with Spark, Delta Lake, and MLflow. Leverage Databricks for data engineering, analytics, and machine learning tasks within application development.
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At least two (2) years of experience with Databricks- Expertise in designing and deploying data applications on cloud solutions, such as Azure or AWS- Comprehensive understanding of data management best practices including demonstrated experience with data profiling, sourcing, and cleansing routines utilizing typical data quality functions involving standardization, transformation, rationalization, linking and matching.
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Experience with cloud data services such as Redshift, Relational database services (RDS), Snowflake and Databricks. Hands on experience in data engineering desired with extensive knowledge of SQL and PySpark, on Databricks Platform.
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. Job Responsibilities:- Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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We are seeking a dedicated and driven Data Engineer with solid experience in Azure Data Platforms and Databricks. Expertly use Azure data services (including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and others) to extract, transform, and load (ETL) data from various sources.
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3+ years’ experience in data administration, from setting up the Databricks environment to successfully administering it. Be able to Install, troubleshoot, integrate with Identity Access Management for Databricks.
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Exhibit expertise in Azure Databricks, Azure Data Lake, Ansible, SQL, Terraform, Kafka, and Azure CLI.Apply hands-on development experience using Databricks, with proficiency in Azure, AWS, or other cloud technologies.
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databricks job Title: data Company: Capgemini
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