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The Lead Data Engineer is responsible for orchestrating, deploying, maintaining and scaling cloud infrastructure targeting big data and platform data management (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using Hadoop or equivalent.
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Cricut® is looking for a Senior Big Data Engineer to join our Data Platform team supporting the future of AI/ML. The ideal candidate will design, build, and integrate data from various resources, and manage big data pipelines that are easily accessible with optimized performance of Cricut®'s big data ecosystem.
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Our client is currently seeking an experienced Data Engineer – Big Data individual for their Midtown office in Atlanta, GA. The successful candidate must have Big Data engineering experience and must demonstrate an affinity for working with others to create successful solutions.
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Strong experience in Amazon EMR/DataBricks/Cloudera CDP Experience with Dask, Numpy, Pandas, Scikit-Learn Hands-on experience in Big Data, Cloudera Distribution 7. Role: Architect Big Data/Hadoop Location: Remote within PST Duration: 6-12 Months Contract Exp: 12 years Note: This position is open for W2 The Big Data Engineer shall lead the Big Data Engineering team.
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Exposure to big data platforms - Snowflake, Redshift, Azure, Matillion, Hadoop. You have a strong background in data quality management and are experienced with SaaS and/or digital sales metrics.
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Technical Proficiency: Expertise in SQL and programming languages such as Python; familiarity with big data technologies like Apache Hadoop, Spark, and Kafka. Professional Experience: At least 5 years of experience in data engineering, with a strong focus on data integration and pipeline construction in cloud environments and enterprise data warehouses like Snowflake.
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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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MS or PhD in statistics, math, computer science, or related quantitative field. You will be expected to lead recommendation and personalization algorithm research, development, implementation, and optimization for product areas, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams.
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big data jobs Company: Ero Locums in Leesburg, District Of Columbia
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