Data Engineering Manager, Sales Data Services (SDS)
Core
Manage a team of data engineers and software developers to own data infrastructure, pipelines, and platform capabilities powering analytics, AI tools, and business-critical applications for Amazon Advertising's Sales teams.
Role type
Senior IC data engineering manager (team lead)
Builds
Data warehousing solutions, ETL/ELT pipelines, and data models serving analytics, data science, and business stakeholders across Amazon Advertising.
Domain
eCommerce advertising, big data, data warehousing
Deliverable
production ML models | product features | dashboards & analysis | infrastructure
Required skills
team leadership and hiring, data platform strategy, Redshift cluster management, ETL/ELT pipeline design, low-latency infrastructure optimization, data governance and quality frameworks, cross-functional partnership, operational excellence and incident response
Preferred skills
Hadoop, Hive, Spark, EMR, AWS tools (S3, EC2)
Technologies
Redshift, Druid, Spark, Hadoop, Hive, EMR, S3, EC2, Python, Java, Scala, NodeJS
Responsibilities
Lead and develop a team of data engineers and SDEs, hiring, mentoring, setting technical direction, managing performance and growth opportunities; Own the data platform strategy and roadmap for the team's portfolio, including multiple Redshift clusters, ETL/ELT pipelines, and data models; Manage and optimize Redshift, druid and low-latency retrieval infrastructure, ensuring performance, cost efficiency, availability, and scalability; Own data pipelines for AI-powered tools, ensuring reliable, high-quality data flows that power the team's GenAI and ML applications; Drive data engineering for business-critical applications, including dashboards and other internal self developed software products; Establish and enforce data governance, quality, and reliability standards, implementing monitoring, alerting, SLAs, and data quality frameworks; Partner cross-functionally with product managers, data scientists, BI engineers, and software engineers to translate business requirements into scalable data architecture and pipeline solutions; Represent data engineering in planning and leadership forums, contributing to annual planning, QBRs, and roadmap reviews; Drive operational excellence, owning on-call processes, incident response, COE follow-ups, and continuous improvement of the team's operational posture
Seniority
Senior, hands-on IC with team management