The person leads a team of data engineers and BI engineers to build scalable data platforms and deliver impactful analytics solutions. The role focuses on testing, evaluating, and deploying the latest AI and machine learning techniques to enhance analytics and decision-making. This leader ensures reliable data pipelines, strong data governance, and high-quality datasets for advanced insights. They collaborate closely with product, business, and science teams to translate business needs into data and AI solutions. The manager also drives best engineering practices, production readiness, and a culture of innovation and measurable impact.

About the team
We are the central data and science org for Amazon's cross border business. We own 50+ core foundational datasets enabling 8+ business workstreams and drive 100+ analytical reports. Our infrastructure will scale 20PB of data in next 3 years and we are moving fast to execute AI readiness for data and analytics. Our platforms will be self-serviceable, agentic with focused attention on scalability, quality and governance. We drive 15+ ML programs to ensure scientific lens for solving critical business problems.

Basic Qualifications

- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience managing a data or BI team
- Experience leading and influencing the data or BI strategy of your team or organization
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience hiring, developing and promoting engineering talent

Preferred Qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)
- Experience working with or evaluating AI systems
- - managing a team driving AI experiments and successfully pushed to production

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