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Your expertise in Airflow, DBT, and Databricks will be essential in optimizing our data workflows and enabling advanced analytics and insights. Develop and manage data models, schemas, and storage solutions in Databricks to support analytical and operational use cases.
$180,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The successful candidate will develop and support a wide variety of data engineering pipelines utilizing tools including Azure Databricks, Azure Data Factory, Azure Data Lake Store and Azure Synapse.
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Extensive experience in Databricks Data engineering Job Runs Data Ingestion and Delta Live Tables. Develops and deploys scalable and efficient data processing pipelines using Azure Data Factory, Azure Databricks, and other relevant technologies.
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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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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. AWS, Docker, Airflow, Databricks.
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Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets.
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Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance. Our team develops, implements, and maintains recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
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Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment. 7+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience.
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Building streaming data pipelines using Kafka, Spark, or Flink. Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve how we do data collection, experimentation and analysis.
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Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day - from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
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In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings. Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.
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Whether that's evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney's unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.
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Proficiency in data warehousing solutions (e.g., Redshift, BigQuery, Snowflake, Databricks) Job Description: We are seeking an experienced and skilled Senior Data Engineer to join our dynamic team.
$110,000 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Qualifications Requirements: Bachelor's degree inputer Science, Information Technology, or a related field Solid experience in Databricks platform, data engineering, and using Delta Live Tables Experience with medallion architecture in a data lake environment Proficiency in Snowflake data warehousing platform Strong understanding of ETL workflows and data pipeline automation.
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Data Integration : Connect Power BI to Azure Databricks, ensuring seamless data integration and real-time analytics capabilities. Solution Design : Architect and design end-to-end data analytics solutions using Power BI and Azure Databricks.
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databricks engineer jobs Title: data engineer Company: Cypress Human Capital Management Llc
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