Data Engineer - Ads Analytics & Data Infrastructure

Amazon Inc.; Asti; Ibrido; EUR 55.000 - 75.000; Tempo pieno

Descrizione del lavoro

Amazon is seeking a motivated Data Engineer to join the DIGI Ad Sales Finance analytics team in Italy. You will partner with Finance and Business leaders to expand and optimize data infrastructure supporting weekly to annual reporting for Display Ads Finance.

The role focuses on building scalable ETL pipelines, data warehousing, and GenAI-ready data layers to automate insights. Collaboration with data scientists and cross-functional teams is essential.

Competenze

• 3+ years of data engineering experience.
• 4+ years of SQL experience.
• Experience with data modeling, warehousing and ETL pipelines.

Mansioni

• Own the design, operations and improvements for the data warehouse infrastructure.
• Maintain, improve and manage all ETL pipelines and clusters.
• Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
• Define metrics and KPIs to measure success of strategic initiatives and report on their progress.
• Develop relationships and processes with finance, sales, business operations, solution delivery team, partner, BD, and other cross-functional stakeholders.
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
• Collaborate with data scientists, BIEs and BAs to deliver high quality data architecture and pipelines.
• Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns.

Conoscenze

Data engineering

SQL

ETL pipelines

Data modeling

Warehousing

Strumenti

Redshift

S3

AWS Glue

EMR

Kinesis

Firehose

Lambda

IAM

Descrizione del lavoro

Amazon is seeking a motivated Data Engineer to join the DIGI Ad Sales Finance analytics team in Italy. You will partner with Finance and Business leaders to expand and optimize data infrastructure supporting weekly to annual reporting for Display Ads Finance.

The role focuses on building scalable ETL pipelines, data warehousing, and GenAI-ready data layers to automate insights. Collaboration with data scientists and cross-functional teams is essential.