Head of Data Engineering & BI for Alexa Audio

Amazon; Seattle (WA); On-site; USD 202,000 - 274,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon in Seattle, WA is seeking a Sr. Manager of Data Engineering and BI to lead a team of 6 engineers and BIEs. You will own end-to-end analytical solutions, scale data infrastructure, and drive reporting for Alexa Audio's key metrics across content types and geos.

You will partner with product, leadership, and partner teams to translate requirements into robust, scalable data architectures, leveraging AWS tools to support diverse use cases and ensure data confidence and reliability.

Qualifications

• 8+ years of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience in Python, Java, Scala or NodeJS.
• 5+ years of delivering results managing a BI/analytics team.

Responsibilities

• Delivery of robust, scalable data solutions across content and geos.
• Enhance reporting and analytics for senior stakeholders.
• Lead data governance, quality standards and SLAs.
• Own ETL/big data pipelines, semantic layers, and dashboards.
• Evolve WBR/MBR reporting and self-service analytics.
• Collaborate with product, BI teams and stakeholders to prioritize work.
• Establish best practices for data engineering and documentation.
• Mentor team members and drive career development.
• Improve data availability and time-to-insight for decision makers.
• Ensure trust and reliability of reported numbers.

Skills

Data engineering

Data modeling

ETL pipelines

Python

Java/Scala/NodeJS

Team leadership

Tools

AWS Redshift

S3

AWS Glue

EMR

Kinesis

IAM

Job description

Amazon in Seattle, WA is seeking a Sr. Manager of Data Engineering and BI to lead a team of 6 engineers and BIEs. You will own end-to-end analytical solutions, scale data infrastructure, and drive reporting for Alexa Audio's key metrics across content types and geos.

You will partner with product, leadership, and partner teams to translate requirements into robust, scalable data architectures, leveraging AWS tools to support diverse use cases and ensure data confidence and reliability.