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Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and implement effective solutions. Nearly every digital consumer experience across the company relies on Identity Platform for mission critical business operations, including streaming video content on Disney+, booking Disney Parks and Resort vacations, playing ESPN Fantasy Football, buying products from Shop Disney and many more.
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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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Experience with data integration platforms is a plus (e.g., Databricks) Data Engineers on the Disney Streaming Machine Learning and Innovation team develop and maintain systems and datasets that are used for Fraud/ATO/Bot Detection on Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. In this role you will partner with Applied Machine Learning Engineers and Data Scientists to help manage and scale processes to create algorithm input features and datasets.
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Lead the design, develop, maintain, ETL (Extract, Transform, Load) processes and data pipelines for rule-based fraud detection system. As part of the team, you will be tackling cutting edge issues that come with cloud-based infrastructures, platform resiliency requirements, security, and data migrations at scale.
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Whether that is 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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As a member of this team you will collaborate across Engineering and Data teams to identify internal and external data sources to design and implement ETL strategy, automation frameworks, and scalable data pipelines.
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Preferred Qualifications: Experience with data integration platforms is a plus (e.g., Databricks)Interested in both backend service development and data analysis#DISNEYTECH The hiring range for this position in New York is $156,300-$209,600 per year.
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Experience on large scale data processing is a MUST. Interested in both backend service development and data analysis. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors.
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A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
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Technologies such as OneTrust, Databricks, Jupyter, Snowflake, Redshift, Airflow, DynamoDB, REDIS, Kubernetes, Kinesis, REST APIsSQL, Python, Scala, other computer software languagesPreferred Qualifications Minimum two years of experience in the technology industry, knowledge of data and product a plus.
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Become proficient across multiple data domains, including internal positions, account performance, market data, security, issuer, ESG, alternative, and trading data. Collaborate with different teams in EDM (Data Cloud, Architecture, Data Governance Tech, Data Science) and support strategic initiatives such as data governance, data-as-a-service, and self-service analytics.
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Spot customers (including some of the most innovative enterprises and startups like Ticketmaster, Duolingo, and Broadcom) use our software to reduce the amount of human effort required to manage their cloud infrastructure for web applications, container workloads, big data processing, and more.
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Utility Relocation Engineering: Involved in relocation plans’ design for highway construction projects including those funded by State DOTs. Other Broadband Design: Studies (Planning, Facilities Integration, Make-Ready, etc.
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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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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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market data every other jobs Company: Masonicare in Anoka, Minnesota
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