Data Engineering Manager, WW FBA Central Analytics
Amazon
Data Engineering Manager, WW FBA Central Analytics
Job Description
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.
Locations
- India, KA, Bengaluru, Bengaluru, KA, India
Salary
Estimated Salary Rangehigh confidence
120,000 - 200,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experienceintermediate
- - 5+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experienceintermediate
- - 5+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experienceintermediate
- - 5+ years of data engineering experienceintermediate
- - Experience managing a data or BI teamintermediate
- - Experience communicating to senior management and customers verbally and in writingintermediate
- - Experience leading and influencing the data or BI strategy of your team or organizationintermediate
- - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJSintermediate
Required Qualifications
- - 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience (experience, 5 years)
- - 5+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience (experience, 5 years)
- - 5+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience (experience, 5 years)
- - 5+ years of data engineering experience (experience, 5 years)
- - Experience managing a data or BI team (experience)
- - Experience communicating to senior management and customers verbally and in writing (experience)
- - Experience leading and influencing the data or BI strategy of your team or organization (experience)
- - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS (experience)
Preferred Qualifications
- - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR (experience)
- - Experience with AWS Tools and Technologies (Redshift, S3, EC2) (experience)
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.
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Data Engineering Manager, WW FBA Central Analytics
Amazon
Data Engineering Manager, WW FBA Central Analytics
Job Description
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.
Locations
- India, KA, Bengaluru, Bengaluru, KA, India
Salary
Estimated Salary Rangehigh confidence
120,000 - 200,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experienceintermediate
- - 5+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experienceintermediate
- - 5+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experienceintermediate
- - 5+ years of data engineering experienceintermediate
- - Experience managing a data or BI teamintermediate
- - Experience communicating to senior management and customers verbally and in writingintermediate
- - Experience leading and influencing the data or BI strategy of your team or organizationintermediate
- - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJSintermediate
Required Qualifications
- - 5+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience (experience, 5 years)
- - 5+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience (experience, 5 years)
- - 5+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience (experience, 5 years)
- - 5+ years of data engineering experience (experience, 5 years)
- - Experience managing a data or BI team (experience)
- - Experience communicating to senior management and customers verbally and in writing (experience)
- - Experience leading and influencing the data or BI strategy of your team or organization (experience)
- - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS (experience)
Preferred Qualifications
- - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR (experience)
- - Experience with AWS Tools and Technologies (Redshift, S3, EC2) (experience)
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.
Tags & Categories
Answer 10 quick questions to check your fit for Data Engineering Manager, WW FBA Central Analytics @ Amazon.
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~2 Minutes
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