Lead Data Engineer, Subscriber Solutions

Disney Cruise Line - The Walt Disney Company
London
6 days ago
Create job alert

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.

About The Role

Subscriber Data Solutions builds and maintains best in class data products enabling business teams to analyze and measure subscriber movements and support revenue generation initiatives. The Lead Data Engineer will contribute to the Company’s success by partnering with business, analytics and infrastructure teams to design and build data pipelines to facilitate measuring subscriber movements and metrics. Collaborating across disciplines, they will identify internal/external data sources, design table structure, define ETL strategy & automated Data Quality checks. You will also help mentor and guide other more junior data engineers in their data pipeline development.

Responsibilities

  • Lead the successful design and implementation of complex technical problems.

  • Lead and contribute to the design and growth of our Data Products and Data Warehouses around Subscriber movements and metrics.

  • Use sophisticated analytical thought to exercise judgement and identify innovative solutions.

  • Partner with technical and non-technical colleagues to understand data and reporting requirements, and collaborate with Data Product Managers, Data Architects and other Data Engineers to design, implement, and deliver successful data solutions.

  • Design table structures and define ETL pipelines to build performant Data solutions that are reliable and scalable in a fast growing data ecosystem.

  • Develop Data Quality checks.

  • Develop and maintain ETL routines using ETL and orchestration tools such as Airflow.

  • Serve as an advanced resource to other Data Engineers on the team, and mentor and coach more junior members of the team helping to improve their skills, knowledge, and productivity.

Basic Requirements

  • 7+ years of data engineering experience developing large data pipelines.

  • Strong understanding of data modeling principles including Dimensional modeling, data normalization principles.

  • Good understanding of SQL Engines and able to conduct advanced performance tuning.

  • Ability to think strategically, analyze and interpret market and consumer information.

  • Strong communication skills – written and verbal presentations.

  • Excellent conceptual and analytical reasoning competencies.

  • Comfortable working in a fast-paced and highly collaborative environment.

  • Familiarity with Agile Scrum principles and ceremonies.

Preferred Qualifications

  • 4+ years of work experience implementing and reporting on business key performance indicators in data warehousing environments, required.

  • 5+ years of experience using analytic SQL, working with traditional relational databases and/or distributed systems (Snowflake or Redshift), required.

  • 3+ years of experience programming languages (e.g. Python, Pyspark), preferred.

  • 3+ years of experience with data orchestration/ETL tools (Airflow, Nifi), preferred.

  • Experience with Snowflake, Databricks/EMR/Spark & Airflow a plus.

Required Education

  • Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.

  • Master’s Degree a plus.

Additional Information

#DISNEYTECH


The hiring range for this position in Santa Monica, California is $152,200 to $204,100 per year, in Seattle, Washington is $159,500 to $213,900 per year, in New York City, NY is $159,500 to $213,900 per year, and in San Francisco, California is $166,800 to $223,600 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.

#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist I, Growth Analytics

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.