Job Posting Title:
Senior Data EngineerReq ID:
10099405Job Description:
Department/Group Overview:
Disney Entertainment & ESPN Technology
On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. 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.
A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology
Building the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.
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.
Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.
Commerce, Growth & Identity (CGI)
The Commerce, Growth & Identity (CGI) team is dedicated to three business-critical areas at Disney that will help transform its media business. They create seamless user experiences for consumers who can choose from a wide range of subscription plans, enabling more choice and flexibility. The CGI team is also focused on building innovative and cutting-edge capabilities that will drive subscriptions, engagement, and monetization across Disney’s streaming and digital products.
Job Summary:
The Search Machine Learning (ML) team powers the ML aspects of search engines for Disney+ and Hulu platforms, in a highly collaborative environment. ML-based services are embedded inside the entire life cycle of search journey, from query understanding, semantic retrieval, and engagement-based re-ranking of contents. Working closely with our core search counterpart team and product stakeholders, we are constantly testing new ideas, and bringing the proven ones into fruition, through experimentation.
In this role, you will be partnering closely with ML engineers/data scientists to help automate and manage their data needs for regular training, and online inference. You will be able to own the entire lifecycle of data pipelines, communicate your requirements with upstream DATA teams, bring your data engineering skills and ideas into life by engineering efficient data pipelines, and help supporting the feature requirements by the ML engineers/data scientists.
Responsibilities and Duties of the Role:
Design and develop offline (batch)/near-line (streaming) data jobs.
Collaborate with ML and data practitioners to automate their pipelines.
Build tooling and low-latency services to enable and support event-driven
Ability to work on multi-faceted projects with engineers from diverse backgrounds, heterogenous skills and across teams.
Work in an Agile environment that focuses on collaboration and teamwork
Required Education, Experience/Skills/Training:
Basic Qualifications
5+ years of software experience, with 3+ years of relevant data and software experience.
Knowledge of the Python/Java data ecosystem.
Experience in building large datasets and scalable services
Experience deploying and running services in AWS, and engineering big-data solutions using technologies like Databricks, EMR, S3, Spark
Experience loading and querying cloud-hosted databases such as Redshift and Snowflake
Experience designing and developing backend microservices for large scale distributed systems using gRPC or REST.
Experience with large-scale distributed data processing systems, cloud infrastructure such as AWS or GCP.
Preferred Qualifications
Knowledge in optimizing Spark jobs.
Experience building streaming pipelines using Kafka, Spark, Kinesis
Mentor colleagues on best practices and technical concepts of building large scale solutions
Required Education
Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work
Job Posting Segment:
Product & Data EngineeringJob Posting Primary Business:
PDE - Engagement Experiences & PlatformsPrimary Job Posting Category:
Data EngineeringEmployment Type:
Full timePrimary City, State, Region, Postal Code:
Santa Monica, CA, USAAlternate City, State, Region, Postal Code:
USA - CA - 2500 Broadway Street, USA - CA - Market St, USA - CT - ESPN Building 13, USA - NY - 1211 Avenue of the AmericasDate Posted:
2024-09-13
0 applies
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