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Utilize programming languages like Python, SQL, and NoSQL databases, Container Orchestration services including Terraform, Docker and Kubernetes, and a variety of Azure tools and services to build an Event Driven Big Data Streaming platform for an ELT data pipeline.
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Strong Experience with cloud-based data warehouses – e.g., Snowflake, Big Query, Synapse, RedShift, etc. In this capacity, the Data Engineer designs and develops systems for the maintenance of the business’s data warehouse, ETL processes, and business intelligence.
$83,000 - $138,200 a yearFull-timeRemoteExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is a plus. As a Staff Data Engineer II at Blitz you will be responsible for designing, developing, and maintaining robust data pipelines and infrastructure.
$180,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The Data Architect/Sr Data Engineer will be responsible for developing Python modules using NumPy multi-dimensional arrays, pandas, and dynamic programming in AWS and Snowflake and expanding and optimizing our ETL and data pipeline architecture and data flow and collection across our Business Portfolio.
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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. 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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AWS, Docker, Airflow, Databricks. 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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5+ years writing production-level, scalable code (e.g. Python, Scala) Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to develop and implement in production algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams.
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Would be preferred to have executed end to end implementation/migration of a Data Warehouse and Big Data (Hadoop) project from on prem to GCP (using Google BigQuery, DataFlow, DataProc etc.
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Proven experience as a Big Data Engineer with a focus on large-scale data processing. We're looking for a self-motivated, highly driven Big Data Engineer to bolster our Data Platform teams.
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Black Canyon Consulting (BCC) is searching for a Sr. Software Developer in Bioinformatics and Big Data to support our work for the National Center for Biotechnology Information (NCBI) at the National Library of Medicine (NLM), an institute of the National Institutes of Health.
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big data jobs Title: engineer Company: Leidos in Danbury, Connecticut
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