Data Engineering Manager, 3PX Analytics & Insights
Core
Lead a data engineering team to own the data infrastructure, pipelines, and platform capabilities powering AWS's Private Pricing analytics, AI tools, and business-critical applications.
Role type
Senior IC data engineering manager (team lead)
Builds
Data platform strategy, Redshift clusters, ETL/ELT pipelines, and data models serving analytics, data science, and business stakeholders.
Domain
Cloud economics, private pricing, and enterprise deal management
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Team leadership and hiring, data platform strategy, Redshift cluster management, ETL/ELT pipeline development, data governance and quality frameworks, cross-functional partnership, operational excellence (on-call/incident response), modern scripting/programming (Python, Java, Scala, NodeJS)
Preferred skills
Big data technologies (Hadoop, Hive, Spark, EMR), AWS tools (S3, EC2)
Technologies
Redshift, Teradata, Netezza, Spark, Hadoop, Hive, EMR, S3, EC2, Oracle, MySQL, MS SQL
Responsibilities
Lead and develop a team of senior data engineers, 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 infrastructure, ensuring performance, cost efficiency, availability, and scalability. Own data pipelines for AI-powered tools, ensuring reliable, high-quality data flows that power 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, 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.