The Walt Disney Company Logo

The Walt Disney Company

Lead Product Software Engineer - Data Systems

Posted 6 Days Ago
Be an Early Applicant
In-Office
New York, NY
156K-214K Annually
Senior level
In-Office
New York, NY
156K-214K Annually
Senior level
Lead design, build, and operate scalable, low-latency data systems and platform services for real-time personalization and recommendations. Partner with ML, product, and platform teams to deliver feature serving, inference integration, APIs, monitoring, and reliability. Provide architecture leadership, mentor engineers, and establish operational standards for data pipelines and ML workflows.
The summary above was generated by AI

Job Posting Title:

Lead Product Software Engineer - Data Systems

Req ID:

10151200

Job Description:

Department/Group Overview:

ESPN Product & Technology

Technology is at the heart of Disney’s past, present, and future. Disney Sports News & Entertainment 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 ESPN’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.

Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.

Job Summary

ESPN is building a new real-time short-form video recommendation system that will be the foundation of our next-generation personalization experience. High-quality data is at the core of this effort. We are seeking a Lead Software Engineer with deep expertise in building scalable distributed systems, platform services, and data-intensive applications that power personalized user experiences. In this role, you will work closely with Software Engineering, Machine Learning, Product, and Platform teams to design and deliver the foundational systems, APIs, data platforms, and infrastructure that support real-time personalization and recommendation services at ESPN scale.

Responsibilities and Duties of the Role:

  • Design, build, and operate highly scalable software systems and services that support content discovery, personalization, and recommendation experiences.
  • Develop and maintain distributed data processing platforms and service architectures that power both online and offline product workflows.
  • Build foundational platform capabilities, including feature serving, model inference integration, experimentation infrastructure, and recommendation delivery services.
  • Design reliable APIs and service interfaces that enable personalization capabilities across multiple ESPN products and surfaces.
  • Lead architecture and technical design efforts for systems that must operate with high availability, low latency, and large-scale traffic demands.
  • Partner with Machine Learning, Data Science, Product, and Platform Engineering teams to translate business objectives into scalable software solutions.
  • Establish engineering standards, operational best practices, monitoring, observability, and reliability mechanisms across critical systems.
  • Drive technical strategy and execution for next-generation personalization platforms and services.
  • Mentor engineers and influence engineering practices across teams through technical leadership, design reviews, and architectural guidance.

Required Education, Experience/Skills/Training:

Basic Qualifications

  • 7+ years of experience building and maintaining production-grade data pipelines and distributed data processing systems
  • Strong experience with modern data processing frameworks such as Spark, Flink, Beam, Kafka Streams, or equivalent.
  • Experience designing and implementing real-time streaming data pipelines.
  • Proficiency with SQL and schema design for large-scale analytical datasets.
  • Familiarity with cloud data platforms (e.g., AWS) and modern data infrastructure components (e.g., data lakes, data warehouses, feature stores).
  • Experience supporting ML workflows (model training pipelines, feature engineering, data validation).
  • Strong knowledge of data quality frameworks and best practices, with hands-on experience using Databricks, Snowflake, and Apache Airflow for data pipeline orchestration and validation.
  • Solid software engineering skills with experience in Python, Java, Scala, or similar languages.
  • Strong problem-solving skills and ability to work independently in a fast-paced environment.

Preferred Qualifications

  • Prior experience building data infrastructure for personalization, recommendation systems, or other ML-powered products.
  • Familiarity with ML lifecycle tools (MLflow, TFX, Kubeflow) and MLOps best practices.
  • Experience implementing data validation, monitoring, and lineage tools (e.g., dbt tests, Snowflake data quality checks) to ensure high data integrity for ML models.
  • Knowledge of real-time ML serving architectures and online feature generation.
  • Experience optimizing large-scale data workflows for latency-sensitive applications.
  • Prior experience operating in 0→1 product development or startup environments.
  • Nice to have experience with tools/technologies such as Databricks, Snowflake, Kafka, AWS SQS, Kubernetes, and related cloud-native data platform components.

Required Education  

  • Bachelor’s or Master’s in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.
The hiring range for this position in CT and CA is $155,700 - $208,700, and in NY is $159,500 - $213,900 per year. 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.

Job Posting Segment:

PE - Sports, News & Entertainment, Tech Enablement

Job Posting Primary Business:

PE - Sports, News & Entertainment, Enablement - Sports Experience Delivery

Primary Job Posting Category:

Product Software Engineering

Employment Type:

Full time

Primary City, State, Region, Postal Code:

New York, NY, USA

Alternate City, State, Region, Postal Code:

USA - CA - 1200 Grand Central Ave

Date Posted:

2026-06-16

Similar Jobs

2 Hours Ago
Remote or Hybrid
140K-165K Annually
Senior level
140K-165K Annually
Senior level
AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development
Create reusable "paved paths" (documentation, reference architectures, IaC modules, code templates, and tools) to simplify building on enterprise platforms. Partner with architects and platform teams, develop and maintain templates and AI-assisted developer workflows, gather feedback from application teams, and iterate to maximize usability and adoption across a large, federated engineering organization.
Top Skills: Agent-Based ToolsAWSAzureCi/CdCloudformation (Cft)GCPInfrastructure As Code (Iac)Internal Developer AssistantsPrompt EngineeringPulumiTerraform
3 Hours Ago
In-Office
138K-194K Annually
Senior level
138K-194K Annually
Senior level
Fintech • Information Technology • Financial Services
The Vice President, Business Manager for Aladdin will oversee workforce planning, manage hiring strategies, and enforce operational discipline within the organization, ensuring alignment with business priorities while improving processes and driving financial management.
Top Skills: CognosExcelPower BISAPTm1Workday
4 Hours Ago
In-Office
100K-120K Annually
Mid level
100K-120K Annually
Mid level
Legal Tech • Other • Professional Services
The Legal Recruiting Coordinator manages various aspects of legal hiring, coordinates interview logistics, reviews resumes, and supports junior recruiting team members. They maintain recruitment data, organize law school programs, and interact with candidates and law professionals.
Top Skills: Microsoft Office Suite

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account