Data Engineer, Prime Video Finance Analytics

Data Engineer

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. The Prime Video Finance Analytics team is looking for an experienced Data Engineer.

The team is embedded within finance alongside content and business finance partners, we own the single-source-of-truth metrics layer that serves both finance and business leadership. Working across AWS technologies, you'll deliver self-service analytics, infrastructure-as-code, and reliable ETL/ELT workflows. You'll work closely with global business partners and technical teams on many non-standard and unique business problems and use creative problem solving to deliver data products that underpin Prime Video strategic decision making, from content selection to on-platform customer experience.

Key job responsibilities:

• Build and optimize data pipelines to ingest and transform data from various sources, including traditional ETL pipelines and event data streams.
• Utilize data from disparate sources to build meaningful datasets for analytics and reporting, focusing on consolidating data from various Prime Video systems.
• Implement big-data technologies (e.g., Redshift, EMR, Spark, SNS, SQS, Kinesis) to optimize processing of large datasets.
• Develop and maintain the team's data platform, including infrastructure-as-code using AWS CDK.
• Work closely with business stakeholders to understand their needs and translate them into technical solutions.
• Analyze business processes, logical data models, and relational database implementations.
• Write high-performing SQL queries.
• Collaborate with software engineers to support the data needs of products.