Data engineer (prime video finance bi team)

Amazon’s Prime Video is a premium on-demand video entertainment service that offers customers the greatest choice in what to watch from popular Amazon Original TV shows such as The Grand Tour, Jack Ryan, The Boys and the recent Golden Globe winning The Marvelous Mrs. Maisel, to Original Movies like the Oscar‑winning Manchester by the Sea and The Salesman. The service also offers TV shows that are exclusively available for Prime members in each country such as American Gods, Mr Robot and Outlander, and more recently live sport including the US Open tennis and Premier League football. Prime Video is at the forefront of the entertainment industry and growing fast – now available in more than 240 countries and territories worldwide – and we work in a dynamic, and exciting 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 BI team is looking for a Data Engineer to help power the data infrastructure behind Prime Video’s strategic and financial decision making. In this role, you will design and build scalable data pipelines and warehouse solutions that underpin business-critical reporting used by leadership worldwide. You’ll partner with upstream technical teams to architect complex data ingestion frameworks for high-priority data sources, and collaborate with Finance and Business stakeholders to translate ambiguous business challenges into well-engineered, automated data solutions. Your work will directly enable the KPIs, metrics, and analytics that drive Prime Video’s content and customer experience strategy forward.

Key Job Responsibilities

The successful candidate will thrive in a fast‑paced, data‑driven environment and be motivated by solving complex engineering problems at massive scale. Excited about building robust, automated data systems that power strategic decision making, the successful candidate will relish the opportunity to drive Prime Video’s data infrastructure to the next level.

Responsibilities

• Design, build, and maintain large‑scale data warehouse architectures and ETL/ELT pipelines that serve hundreds of users globally, ensuring high availability, performance, and data integrity.
• Apply cloud‑based AWS services (Redshift, Glue, EMR, S3, Lambda, Step Functions) to solve challenging problems around big data processing, data warehouse design, and self‑service data access.
• Develop automated data quality detection frameworks and monitoring systems to ensure data accuracy, completeness, and timeliness across critical datasets.
• Build and maintain infrastructure as code (CloudFormation, CDK, Terraform) to enable repeatable, version‑controlled deployment of data platform resources.
• Gather technical and business requirements from stakeholders in Finance and Business teams, and translate them into scalable, automated, and well‑engineered data solutions.
• Develop efficient systems and tools to process data at scale, using technologies that accommodate seasonal spikes and future growth.
• Drive automation and optimization across all areas of DW/ETL maintenance, deployment, and operational excellence.
• Build strong partnerships with Business Intelligence, Core Analytics Tooling, and upstream data teams to enhance data sources, improve data models, and enable more scalable and accurate downstream reporting.
• Provide technical guidance on data modeling best practices, pipeline design patterns, and platform capabilities to support informed decision making across Prime Video.

Basic Qualifications

• 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.

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