Technical Program Manager, Level 4

Snap Snap · Consumer · Los Angeles, CA +2

This role is for a Technical Program Manager (TPM) at Snap, focusing on leading complex, cross-functional programs related to AI products. The TPM will be a single-threaded owner, driving programs from ideation to execution, partnering with engineering and product leadership, and using data analytics to guide decisions. The role requires hands-on technical skills, including Python and SQL, and experience with data visualization and automation tools. The TPM will contribute to the technical ecosystem by building automation, improving internal systems, and driving operating rhythm for scale, cost-consciousness, and performance.

What you'd actually do

  1. Lead complex, cross-functional programs that span multiple engineering organizations and require deep technical understanding, rigorous execution, and strategic influence.
  2. Operate as a single-threaded owner (STO) for the most critical programs, managing ambiguity, dependencies, and alignment across diverse technical teams.
  3. Own the full lifecycle of programs—from ideation to execution to operational excellence—delivering outcomes that support Snap’s product, infrastructure, and platform goals.
  4. Partner directly with engineering and product leadership to shape roadmaps, influence technical decisions, and drive accountability.
  5. Use hands-on data analytics (Python, SQL, dashboards, notebooks) to guide programs with data, uncover insights, and communicate clearly with senior stakeholders.

Skills

Required

  • Bachelor's in a technical field such as computer science, mathematics, statistics or equivalent years of experience
  • 2 + years of experience spanning Engineering / Data Science / Technical Program Management leading cross-functional efforts in the software or tech industry in a data-driven environment.
  • A proven track record of leading large-scale, ambiguous programs across distributed teams in fast-paced, cross-functional environments, especially in the areas of improving platform reliability, operational stability and performance of production systems
  • Strong proficiency with Python and SQL, and experience using data to analyze systems, build tools, or inform decisions.
  • Experience with data visualization tools (e.g. Grafana, Looker, Tableau) building dashboards, source control (e.g. GitHub), ticket management (e.g. JIRA).
  • Experience working directly with engineers and contributing to technical design, architectural trade-offs, and roadmap planning.
  • Comfort operating with high visibility and accountability; you thrive on ownership and impact.
  • Demonstrated ability to quickly learn new domains, systems, and technologies.
  • Excellent communication, organizational, and leadership skills.

Nice to have

  • A background in software engineering, infrastructure systems
  • Prior hands-on experience with big data technologies such as Spark, Airflow, Hive, Kafka, or Flink.
  • Familiarity with cloud-native infrastructure (e.g., AWS, GCP) and containerization tools like Kubernetes or Docker.
  • Background in building internal tools or developer platforms to improve engineering velocity and system reliability.
  • Experience managing production systems, reliability initiatives, or cost optimization programs.
  • Exposure to high-scale consumer technology or social platforms with strong privacy, performance, or safety requirements.
  • Strong storytelling and presentation skills—especially with senior engineering or executive audiences.
  • Masters or PhD in a highly analytical field

What the JD emphasized

  • deep technical understanding
  • rigorous execution
  • strategic influence
  • single-threaded owner
  • managing ambiguity
  • dependencies
  • alignment
  • technical decisions
  • drive accountability
  • hands-on data analytics
  • guide programs with data
  • uncover insights
  • communicate clearly with senior stakeholders
  • building automation tools
  • improving internal systems
  • platform-wide transformation
  • operating rhythm of the business
  • engineering systems scale effectively
  • cost-conscious
  • performant
  • proven track record of leading large-scale, ambiguous programs
  • fast-paced, cross-functional environments
  • improving platform reliability
  • operational stability
  • performance of production systems
  • Strong proficiency with Python and SQL
  • using data to analyze systems
  • build tools
  • inform decisions
  • Experience with data visualization tools
  • building dashboards
  • source control
  • ticket management
  • Experience working directly with engineers
  • contributing to technical design
  • architectural trade-offs
  • roadmap planning
  • Comfort operating with high visibility and accountability
  • thrive on ownership and impact
  • Demonstrated ability to quickly learn new domains, systems, and technologies
  • Excellent communication, organizational, and leadership skills