Data Engineering Manager, Specialist Technology Team

Amazon Amazon · Big Tech · Austin, TX · Software Development

Data Engineering Manager to build and lead the data engineering and business intelligence function for AWS Specialist Technology Team (STT). The role will own the centralized data infrastructure that measures the efficacy and impact of the product portfolio and drive the evolution from static reporting into an ecosystem of intelligent, agent-powered data experiences. The team will build and ship customer-facing engineered solutions that accelerate AWS service adoption across industries.

What you'd actually do

  1. Define and own the data strategy and centralized architecture for the organization—connecting product telemetry, usage metrics, and business outcomes into a coherent, scalable data ecosystem
  2. Partner with Product Teams and senior leaders to establish measurement frameworks that quantify product efficacy and business impact, enabling data-driven investment decisions across the portfolio
  3. Lead the evolution from static dashboards toward agentic data systems that allow AI to surface insights within existing field team workflows
  4. Build, manage, and develop a high-performing team of Business Intelligence Engineers and Data Engineers, maintaining a high hiring bar and fostering a culture of operational excellence
  5. Partner with product management, engineering, and field leadership to ensure data infrastructure meets stakeholder needs and answers the right business questions

Skills

Required

  • 4+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes)
  • 2+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL)
  • Experience managing a data or BI team
  • 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

Nice to have

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience with AWS Tools and Technologies (Redshift, S3, EC2)
  • Knowledge of software development life cycle or agile development environment with emphasis on BI practices
  • Experience and demonstrated industry leadership in the fields of database or data warehousing, data sciences and big data processing
  • Experience building data infrastructure supporting AI/ML pipelines or agentic systems

What the JD emphasized

  • agent-powered data experiences
  • agentic data systems
  • applying generative AI and agentic technologies

Other signals

  • AI-powered, on-demand expertise
  • agent-powered data experiences
  • applying generative AI and agentic technologies