Data Engineer III, Amazon 1P Credito, Payments

Amazons Digital Payments & Emerging Markets (DEP) team is awash in data! Every transaction checkout and payment interaction generates a signal and to help make sense of it all our Data Engineering team builds and maintains the data infrastructure that powers payment experiences for millions of customers across emerging countries (Brazil Mexico Australia Singapore and more). We enable the Payments org to make data-driven decisions that improve conversion reduce the cost of payments detect fraud and deliver seamless secure and localized payment experiences at scale.

We build and operate automated self-service data solutions and analytics infrastructure that empower Product Science BI and ML teams to move fast measure results and continuously innovate. As platform builders we are committed to constructing flexible reliable and scalable solutions democratizing data access through self-service tools while protecting a robust high-availability core data experience for all internal customers. Our goal is to empower every team in Payments to make data-driven decisions and effectively measure their impact through high-quality high-availability data.

If you love the challenges that come with big data then this role is for you. We collect billions of payment and behavioral events a day manage petabyte-scale data on Redshift and S3 and develop data pipelines using Spark/Scala EMR SQL-based ETL and Airflow. We are looking for a talented enthusiastic and detail-oriented Data Engineer who knows how to take on big data challenges in an agile way.

Youll help build Digital Payments most important data pipelines and datasets and expand self-service data knowledge and capabilities across the org. Youll partner with Product Science BI and ML teams to build new behavioral events pipelines datasets models and reporting that support their initiatives while continuing to develop and scale our big data pipelines.

Key job responsibilities
Big data design analysis data modeling and the development deployment and operation of large-scale data pipelines.

Manage the data exchange store (Data Lake) and the EMR/Spark processing layer using Airflow as the orchestrator.

Build and protect a robust self-service core data experience for internal customers across key business domains (e.g. payment conversion fraud and regional payment methods).

Partner with Product Marketing BI and ML teams to deliver new events pipelines datasets models and reporting.

Work hands-on with AWS technologies including Redshift S3 EMR EC2 DynamoDB Kinesis Firehose and Lambda.

- Experience as a Data Engineer or in a similar role
- Experience with data modeling warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language such as Python Java Scala or NodeJS
- Experience mentoring team members on best practices

- Experience with big data technologies such as: Hadoop Hive Spark EMR
- Experience operating large data warehouses

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