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[Remote-Position] Disney Data Entry Jobs No Experience $21/Hour

100% Remote Full-time Open now

Ready to take the next step in your career? Join us as a Disney Data Entry No Experience $21/hour Submit Your Application! This role is 100% remote, giving you full control over your work environment. This position requires a strong and diverse skillset in relevant areas to drive success. This straightforward role comes with a dependable salary of a competitive salary.

 

 

Lead Data Engineer Hiring Organization: Disney... Location: San Francisco, CA Employment Type: Full-Time Work Hours: 8 hours per day Salary: $24/hour Job Overview: The Disney Streaming Services (DSS) team under Disney Entertainment & ESPN Technology (DE&ET) is seeking a Lead Data Engineer to join our Information and Analytics group. This team is critical to informing strategic decisions on content development, pricing strategies, advertising effectiveness, customer engagement, and market expansion. We are looking for an enthusiastic data engineer with a strong technical foundation to drive data solutions that empower Disney's growth in online streaming services. Responsibilities: Data Product Development: Contribute to the design and expansion of our data products and data warehouses focused on customer engagement, retention analysis, and data science initiatives. ETL Pipeline Development: Build scalable data warehousing solutions, including creating ETL (Extract, Transform, Load) pipelines for big data environments (cloud, on-premises, or hybrid). Data Engineering Solutions: Design data architectures and models for our core data warehouses and data marts. Collaboration: Work closely with data product managers, data architects, and engineers to implement and deliver high-impact data solutions. Documentation & Data Governance: Maintain detailed documentation of data workflows and ensure adherence to data quality standards. Operational Efficiency: Ensure the reliability and performance of data solutions, meeting SLAs and supporting key data needs of teams like Data Science and Analytics. Agile Practices: Actively participate in agile and scrum processes to promote continuous improvement within the team. Key Qualifications: SQL Proficiency: Strong skills in SQL with the ability to write complex queries for data extraction and to build performant datasets. Experience with Distributed Systems: Hands-on experience with distributed systems, such as Spark and Hadoop (HDFS, Hive, Voila, PySpark), for data querying and processing. Programming Skills: Proficient in Python and Java or Scala. MPP/Cloud Databases: Experience with at least one major MPP (Massively Parallel Processing) or cloud database technology (e.g., Snowflake, Redshift, BigQuery). Data Integration & Pipelines: Strong background in data integration toolsets (e.g., Apache Airflow) and experience in building and maintaining data pipelines. Data Modeling & Warehousing: Skilled in data modeling techniques and knowledgeable about standard data warehousing practices. Agile Methodology: Familiarity with agile and scrum methodologies. Analytical & Communication Skills: Problem-solving skills, attention to detail, strong analytical abilities, and excellent interpersonal skills. Preferred Experience: Familiarity with cloud technologies, especially AWS (S3, EMR, EC2). Benefits: Competitive hourly rate of $24 Work in an innovative team shaping the future of Disney s streaming services Opportunity to work with cutting-edge data technology in a collaborative and dynamic environment About Disney Streaming Services (DSS): At Disney, data is vital for all decision-making processes. We use data to enhance our content offerings, boost customer satisfaction, and drive new business initiatives. Joining our team provides the unique opportunity to work on data-driven solutions that make a direct impact on our products and services worldwide. If you are passionate about big data and are ready to innovate with one of the world s leading entertainment companies, apply today and become part of Disney s streaming future Apply Job!

 

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