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Experienced Full Stack Data Engineer – Cloud-Based Data Pipeline Development and Support

Work from home Full-time role Hiring

Join arenaflex, a leading entertainment and media conglomerate, in a remote data engineering role that offers a unique blend of technical challenge and creative fulfillment. At arenaflex, we're not just a company – we're a community of innovators, storytellers, and problem-solvers who come together to create magical experiences for our guests. Our Disney Choice Science + Mix (DDSI) association is at the forefront of this effort, supporting clients across the arenaflex organization, including Disney Parks, Experiences and Products, Disney Media Networks, and ESPN. As a key member of our team, you'll have the opportunity to work on high-impact projects that drive business value and shape the future of entertainment.

About arenaflex

arenaflex is a global leader in the entertainment and media industry, with a rich history of innovation and creativity. From the iconic Disney Parks to the beloved Disney, Pixar, Marvel, and Star Wars brands, we're known for our ability to bring people together through storytelling and immersive experiences. Our commitment to innovation and technology has enabled us to stay ahead of the curve, and we're now seeking a talented data engineer to join our team.

Job Summary

We're seeking an experienced full stack data engineer to join our DDSI Information Designing (DE) group. As a data engineer, you'll be responsible for the development and support of data pipelines and datasets for our Media business. This is a remote role that offers a unique blend of technical challenge and creative fulfillment, with opportunities to work on high-impact projects that drive business value.

Key Responsibilities

* Develop and maintain data pipelines and datasets for our Media business

  • Collaborate with cross-functional teams, including Choice Science, Client, and Innovation colleagues, on various projects and initiatives
  • Design and implement data pipelines and datasets using ETL/ELT tools and technologies
  • Develop and maintain automated workflows and schedulers to ensure data quality and integrity
  • Work with large datasets and big data technologies, including cloud-based platforms like Snowflake and Databricks
  • Collaborate with data scientists and analysts to deliver high-quality datasets and insights
  • Develop and maintain documentation and knowledge base for data pipelines and datasets

Essential Qualifications

* Bachelor's degree in Computer Science, Mathematics, Engineering, or related field

  • 2+ years of experience in ELT/ETL data pipeline development and support
  • Strong experience with Python and SQL, with a focus on Snowflake and PostgreSQL
  • Experience with cloud-based platforms, including AWS and Azure
  • Experience with source control tools, including GitLab and GitHub
  • Experience with Docker and containerization

Preferred Qualifications

* Experience working with large datasets and big data technologies, including cloud-based platforms like Snowflake and Databricks

  • Experience with data visualization tools, including Tableau and Power BI
  • Experience with machine learning and artificial intelligence technologies
  • Experience with agile development methodologies and DevOps practices
  • Experience with cloud-based data warehousing and business intelligence platforms

What We Offer

* Competitive salary and benefits package

  • Opportunity to work on high-impact projects that drive business value
  • Collaborative and dynamic work environment
  • Professional development and growth opportunities
  • Flexible work arrangements, including remote work options
  • Access to cutting-edge technologies and tools
  • Recognition and rewards for outstanding performance

How to Apply

If you're a motivated and talented data engineer looking for a new challenge, we encourage you to apply for this exciting opportunity. Please submit your resume and cover letter, highlighting your relevant experience and qualifications. We can't wait to hear from you!

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