Senior Manager (data Engineering Team) – Field Cto / Applied Field Engineering

Snowflake Snowflake · Data AI · Sydney, Australia · Solution Engineering

Senior Manager to lead a team of Data Engineering Field CTOs, focusing on helping strategic customers design, build, and optimize next-generation data and AI architectures on Snowflake. The role involves people leadership, technical oversight, and advising customers on data engineering and AI strategies, with a strong emphasis on operationalizing AI/ML workloads like LLMs, RAG, and feature stores.

What you'd actually do

  1. Build, manage, and mentor a world-class team of Field Data Engineers, fostering an inclusive, high-performance culture that champions diversity, psychological safety, and professional growth.
  2. Partner with sales leadership and strategic customers to tackle complex data engineering and AI workloads, ensuring successful onboarding and architectural excellence on Snowflake.
  3. Establish clear goals, drive accountability, and celebrate impact, enabling your team to execute efficiently across multiple sub-regions and time zones.
  4. Serve as a trusted advisor to both technical contributors and C-level executives, translating complex data engineering, streaming, and AI concepts into business value.
  5. Act as a critical feedback loop between the field and engineering, collaborating closely with Product Management to shape the future of Snowflake’s data engineering and AI capabilities based on global market needs.

Skills

Required

  • People management
  • Technical leadership
  • Data Engineering
  • AI/ML workload operationalization
  • LLMs
  • RAG
  • Feature stores
  • Data integration patterns
  • Streaming data ingestion
  • Data pipeline orchestration
  • SQL
  • Python
  • Scala
  • Presentation skills
  • Communication skills
  • Customer relationship management
  • Technical gap assessment
  • Solution articulation

Nice to have

  • Master's degree in Computer Science, Engineering, Mathematics, or a related technical field

What the JD emphasized

  • 5+ years of experience directly managing and scaling high-performing technical teams
  • Experience managing and scaling geographically distributed teams
  • Strong understanding of modern data engineering ecosystems, advanced analytics, and the operationalization of AI/ML workloads such as LLMs, RAG, and feature stores.

Other signals

  • AI-native thinkers
  • operationalization of AI/ML workloads
  • AI strategies