Sr. Manager, Data Engineering Insights

Job Description

We are looking for a Data Engineering Insights Senior Manager to build a team to identify and drive key analytics and engineering initiatives that improve Disney Streaming's engineering ecosystem. You will be a crucial member of the Ecosystem Reliability Engineering team and report to the Director of Engineering, Insights. Ecosystem Reliability Engineering reports directly to Disney Streaming's CTO and is responsible for improving the reliability, performance, and user experience across Disney+, ESPN+, and Hulu. You will be responsible for leading the Engineering Insights team of analytics and engineering members in successful delivery of data driven solutions and recommendations. The analysis and insights your team creates will help drive engineering initiatives and priorities.

You will need a robust data analysis background, be a quick and data-driven learner, have proven data engineering and system design skills, and the ability to lead large multi-disciplinary, cross-functional teams. The ideal candidate will be able to lead and inspire others, while having a strong background in distributed data processing, have great and demonstrable data intuition, be knowledgeable about best practices, and share our passion for continuously improving the ways we use data to make the Disney Streaming better.

Who You Are:
• Passionate about intuitive data models and an expert in distributed data processing patterns
• Advanced in SQL - ability to write complex queries from scratch from multiple tables, creating the appropriate joins, extracting and manipulating data, formatting fields, creating new measures and metrics etc.
• Experience with Databricks
• Excel at taking vague requirements and crystallizing them into executable insights
• Excited about operating independently, demonstrating engineering excellence, and learning new technologies and frameworks to improve our customer experience by harnessing data
• 5+ years' work experience using SQL and ability to run advanced statistical modelling and testing in Scala
• 5+ years of managing high performing teams
• 10+ years of analytical experience
• Experience building multiple concurrent projects of high technical complexity
• In depth understanding of advanced statistical techniques and methodologies as well as multicollinearity regression analysis, ML concepts, and model building

Responsibilities:
• Direct Engineering Insights team to map and document streaming process and job workflow to understand engineering ecosystem and user journeys
• Define KPIs to measure/benchmark ecosystems overall resilience, performance, and user experience
• Oversee development of models to identify, analyze, prioritize, and solve for reliability and performance events
• Manage creation of a monitoring system to manage unsupervised engineering events
• Recruit and hire talented analytics and engineering team members

Basic Qualifications:
• 10+ years of experience in an engineering, data analysis or similar role
• 5+ years of management experience
• Familiarity with SDLC processes
• Strong analytical skills and innate curiosity to troubleshoot and dive deep into complex technical issues, underscoring iteration to identify insights and communicate them effectively to executive leadership
• Experience using data and analytical skills to derive key performance insights in a complex ecosystem
• Experience of identifying key value drivers in a direct-to-consumer application
• Excellent written and verbal executive communication
• 5+ years' work experience using SQL and Python/R or other statistical programming languages
• High familiarity with recent data platforms such as Databricks and Scala
• Highly skilled in statistics concepts (e.g., hypothesis testing, A/B testing, regression analysis, clustering, anomaly detection)
• Familiarity with data exploration and data visualization tools like Tableau, Looker, Chartio, etc.

Preferred Qualifications:
• 2+ years of experience in streaming industry, knowledge of client and server-side architecture a plus
• 3+ years of Python, Spark, Pyspark or Scala
• Master's degree in computer science or equivalent and 5 or more years of related experience in application development and Data Analytics

Required Education
• BA or BS in a quantitative field (Business, Math/Statistics, Economics, CS, Engineering, or similar)

About Disney Streaming:

Comprised of the Company's international business units and various direct-to-consumer streaming services, Disney Media & Entertainment Distribution (DMED) aligns technology, media distribution and advertising sales into a single business segment to create and deliver personalized entertainment experiences to consumers around the world.

About The Walt Disney Company:

The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: media networks, parks and resorts, studio entertainment, consumer products and interactive media. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney's stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.

This position is with Disney Streaming Technology LLC, which is part of a business segment we call Disney Streaming.

Disney Streaming Technology LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney fosters a business culture where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a rapidly changing world.

Jobcode: Reference SBJ-d91y5z-18-225-31-159-42 in your application.