Lead Data Engineer

The Disney Decision Science and Integration (DDSI) is the Walt Disney Company’s center of excellence for developing and deploying innovative analytics that support decision making for client organizations across The Walt Disney Company (TWDC), including Disney Media & Entertainment Distribution (e.g., ABC, ESPN, FX, Studio Entertainment, Disney Theatrical Group) and Parks, Experiences & Products. To drive business value through decision-shaping analytics, DDSI leverages technology, optimization, simulation, statistics and machine learning models to explore opportunities and deploy new analytical capabilities. The Decision Science Product team leverages technology, data analytics, optimization, statistical and econometric modeling to identify opportunities to inform business decisions and drive value for our internal business partners. The team works to understand our partners’ business problems, workflows, technical systems, and data to deliver products ranging from straight-forward analytics insights to complex, fully-integrated analytics solutions.

The Decision Science Product team resides within the Disney Decision Science + Integration (DDSI) organization. DDSI provides internal consulting services for clients across The Walt Disney Company. The DDSI team sits at the intersection of business strategy, advanced analytics, and technology integration to help our partners explore opportunities for analytics, shape business decisions, and drive value. Our work includes conceptualizing new solutions, solution design, custom code engineering / application development, implementation and integration with business processes and technologies.

The successful candidate will be data-driven and business-minded, and will be passionate about solving business opportunities through data analysis and application development. In this position, you will transform data into meaningful business insights and recommended actions. The role will include working with analytically minded peers, where you are expected to contribute to and challenge the current knowledgebase. You will lead improvements of existing solutions or development of new solutions by scoping, implementing, and testing these solutions in order to address business problems. You should enjoy connecting with clients to brainstorm ways to better support business decisions, being a thought leader in analytical settings, solving high-value complex problems, and managing / improving software systems.
 

Responsibilities:

• Act as a Company-wide consultant leveraging knowledge of existing data structures and business knowledge to solve problems.

• Own the vision for analytical systems (or subsystems), be accountable for integrating these systems into existing business processes and software, and define and maintain the consolidated product roadmap for future ongoing evolution of these systems.

• Be an expert in the data; including source systems, design data integration solutions, data validation, and data testing processes.

• Be an expert in our applications; understand how our systems and applications receive data, how it is stored and used, and the underlying processes that leverage it.

• Be a problem solver; when presented with new challenges, you are expected to research and network to find solutions.

• Develop custom-code solutions that are production-ready; when a solution is needed for a specific business problem, support the full application lifecycle.

• Be a hands-on data expert who writes new/custom SQL and Python to extract, translate, and load data (ETL)

• Seek out answers to business problems, and look for opportunities to automate processes.

• Collaborate with partners in Data Engineering, App Engineering, and Decision Science throughout the development process to ensure products are built cohesively

• Proactively communicate with technical and non-technical stakeholders, seek to learn and understand, and potentially challenge existing processes in order to continuously seek improved efficiencies.

Required Qualifications:

• Must have 3+ years of progressively complex experience in software or data engineering - professional experience not just academic

• 3+ years experience with Python

• 4+ years experience with SQL

• 2+ years experience with cloud based technologies, preferably AWS EMR, EC2, and S3

• 2+ years leveraging, designing and/or building relational databases (preferably Postgres or Snowflake)

• 2+ years of experience using Gitlab/Github

• 2+ years of experience using Docker

• Experience working with large datasets and big data technologies, preferably cloud-based, such as Snowflake, Databricks, or similar

• Experience using Apache Airflow

• Proven ability to leverage best practices around data engineering application development processes

• Experience with cloud-based application development and deployment

• Demonstrated excellent written and verbal communication skills

• Demonstrated excellent interpersonal skills, including ability to partner with others and build consensus in a cross-functional team toward a desired outcome

• Proven ability to organize and prioritize work

• Ability to adapt to a rapidly changing business environment and priorities

• Advanced proficiency with multiple client- or internal systems and databases

• Experience delivering custom-written code across multiple product environments (Development to Production)

• Proficient in a variety of data science methods, scalable infrastructure setup, software development, and system architecture plus a basic understanding of system design / architecture

Preferred Qualifications:

• Knowledge of the fields of revenue management, advertising technology (AdTech), and/or pricing strategies

• Knowledge of Media Ad Sales (Linear and/or Digital)

• Strong understanding of advanced analytical methods

• Experience developing short- and long-term product roadmaps for implementation and sustainment

• Technical expertise applied to rapidly changing, highly agile requirements

• Proficiency in automating and improving existing processes

• Knowledge of machine learning methods

• Experience with Nielsen audience data or similar

• Experience with or understanding of Data Management Platforms

Required Education:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Finance, Economics, Data Mining, Analytics, Statistics, or other quantitative field; Master's Degree preferred.