Data Engineer, Prime Video Finance Analytics

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.

Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience with data modeling, warehousing and building ETL pipelines
• Knowledge of distributed systems as it pertains to data storage and computing
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
• Experience as a Data Engineer or in a similar role
• Experience with SQL

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience working on and delivering end to end projects independently

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., Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.