Data Engineer II

Job-Zusammenfassung:

Disney Entertainment and ESPN Product & Technology

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally. 

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.  

Here are a few reasons why we think you’d love working here: 

Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come. 

Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.  

Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems. 

Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms. 

Job Summary:

The Commerce Data Pipelines team for the Data organization within the DEET organization is in search of a Data Engineer II.  As a member of the Commerce Data Pipelines team you will establish the foundational set of data pipelines and datasets which are a vital key to success – enabling dozens of engineering and analytical teams to unlock the power of data to drive key business decisions and provide engineering, analytics, and operational teams the critical information necessary to scale the largest streaming service.  Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.  The Commerce Data Pipelines is seeking to grow their team of world class Data Engineers that share their charisma and enthusiasm for making a positive impact!

Responsibilities and Duties of the Role:

• Contribute to maintaining, updating, and expanding existing Commerce Data platform data pipelines in Scala and Python / Spark while maintaining strict uptime SLAs

• Extend functionality of current Commerce Data platform offerings, including metadata parsing, extending the metastore API, and building new integrations with APIs both internal and external to the Data organization

• Implement the Lakehouse architecture, working with customers, partners, and stakeholders to shift towards a Lakehouse centric data platform

• Implementation shared libraries in Scala and Python that abstract complex business logic to allow consistent functionality across all data pipelines across the Data organization

• Tech stack includes Airflow, Spark, Databricks, Delta Lake, Snowflake, Scala, Python

• Collaborate with product managers, architects, and other engineers to drive the success of the Commerce Data platform

• Contribute to developing and documenting both internal and external standards and best practices for pipeline configurations, naming conventions, partitioning strategies, and more

• Ensure high operational efficiency and quality of the Commerce Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams)

• Be an active participant and advocate of agile/scrum ceremonies to collaborate and improve processes for our team

• Engage with and understand our customers, forming relationships that allow us to understand and prioritize both innovative new offerings and incremental platform improvements

• Maintain detailed documentation of your work and changes to support data quality and data governance requirements

Required Education, Experience/Skills/Training:

Basic Qualifications

• 3+ years of data engineering experience developing large data pipelines

• Strong algorithmic problem-solving expertise

• Strong fundamental Scala and Python programming skills

• Basic understanding of AWS or other cloud provider resources (S3)

• Strong SQL skills and ability to create queries to analyze complex datasets

• Hands-on production environment experience with distributed processing systems such as Spark

• Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines

• Some scripting language experience

• Willingness and ability to learn and pick up new skillsets

• Self-starting problem solver with an eye for detail and excellent analytical and communication skills

Preferred Qualifications

• Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query)

• Experience in developing APIs with GraphQL

• Deep Understanding of AWS or other cloud providers as well as infrastructure as code

• Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices

• Familiar with Scrum and Agile methodologies

Required Education:

Bachelor’s Degree in Computer Science, Information Systems equivalent industry experience

The hiring range for this position in New York, NY is between $112,000 - $150,100. 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. 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.