Data Engineering Manager, WW FBA Central Analytics

Amazon; Asti; In loco; EUR 70.000 - 90.000; Tempo pieno

Descrizione del lavoro

A global e-commerce giant is seeking a Data Engineering Manager to lead a high-performing analytics team in Italy. The role involves managing ETL processes, collaborating with stakeholders, and establishing best practices. Ideal candidates have over 5 years of experience with big data technologies and team management. Join us to help transform data into insights for business growth.

Competenze

• 5+ years of processing data with a massively parallel technology experience.
• 5+ years of relational database technology experience.
• 5+ years of developing and operating large-scale data structures experience.
• Experience managing a data or BI team.
• Experience communicating to senior management.

Mansioni

• Own technical delivery and leadership for scalable ETL pipelines.
• Collaborate with stakeholders to prioritize work aligned with business goals.
• Establish best practices for data engineering.
• Drive team growth through mentoring and coaching.
• Partner with teams to align data governance.

Conoscenze

Big data processing

Relational databases

ETL/ELT processes

Team management

Communication

Programming in Python

Strumenti

AWS Redshift

Apache Spark

Hadoop

Descrizione del lavoro

Data Engineering Manager, WW FBA Central Analytics

Worldwide Fulfillment by Amazon (WW FBA) empowers millions of sellers to scale globally through Amazon's leading fulfillment network. FBA sellers deliver fast, reliable Prime-eligible shipping and hassle-free returns to customers worldwide—enabling them to focus exclusively on business growth while Amazon handles operational logistics. The WW FBA Central Analytics team architects and maintains data infrastructure that delivers critical insights to WW FBA leadership. This team forms strategic partnerships across global product, program, and technology teams to unify datasets, implement self-service analytics platforms, and develop AI capabilities that transform raw data into insights.

We are seeking a Data Engineering Manager who will lead a high-performing analytics team that supports WW FBA’s core metrics and reporting —providing the critical data foundation for business reviews, operational insights, and dashboards that inform WW FBA decisions. You will manage a team of Data Engineers, BIE, and Business Analysts, coordinating execution and driving high standards for data quality, delivery velocity, and operational excellence.

Key job responsibilities

• Own technical delivery and team leadership for development and maintenance of scalable ETL pipelines, semantic layers, and dashboard data models.
• Collaborate with Program Managers, BI teams, and stakeholders to prioritize work aligned with FBA business goals.
• Establish best practices for data engineering, including code reviews, testing, monitoring, and documentation.
• Drive team growth through mentoring, coaching, and career development.
• Partner with the GenAI platform team to align data governance, schema standardization, and data contracts where applicable.

Basic Qualifications

• 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
• 5+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience
• 5+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
• 5+ years of data engineering experience
• Experience managing a data or BI team
• Experience communicating to senior management and customers verbally and in writing
• 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

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with AWS Tools and Technologies (Redshift, S3, EC2)

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