Principal Software Engineer, Data Platform

ServiceTitan ServiceTitan · Enterprise · India Bangalore · Remote

ServiceTitan is seeking a Principal Software Engineer to own the semantic model architecture for their Data & Reporting Platform. This role involves designing and evolving the semantic layer, enabling data products like Reporting and Agentic Analytics, and ensuring performance, scale, and governance. The engineer will also lead technical initiatives and leverage AI coding tools.

What you'd actually do

  1. Design and evolve the semantic modeling layer that serves as the single source of truth for metrics, dimensions, entities, and business logic across all data products.
  2. Architect how the semantic layer is consumed across distinct product surfaces such as Reporting (high-performance BI platform for customers), and Agentic Analytics (metadata-rich, discoverable interfaces that enable AI agents to reason over and query the semantic layer).
  3. Own query performance, materialization strategies, pre-aggregation patterns, and cost optimization.
  4. Build the semantic layer as a true platform experience: self-service metric onboarding, developer-friendly abstractions, clear documentation, data validation, and governance guardrails.
  5. Operate as a technical leader across the Data & Reporting Platform organization.

Skills

Required

  • 10+ years of experience in Software Engineering or Data Engineering roles
  • Deep experience with semantic modeling, data engineering, data lakehouse, and data product development.
  • Track record of building platform-level abstractions consumed by multiple product teams.
  • Strong experience with the DBT ecosystem.
  • Expert-level SQL and Python skills.
  • Experience with query optimization, materialization strategies, and performance tuning at scale.
  • Experience with modern data platform technologies: Snowflake, ClickHouse, or similar OLAP/columnar engines.
  • Familiarity with Spark and streaming platforms (Kafka, Kinesis).
  • Experience designing APIs and interfaces for domain specific data products.
  • Demonstrated proficiency with AI coding tools (eg Claude, Cursor) as part of your regular engineering workflow
  • Experience leading the architecture and design of systems (architecture, design patterns, reliability, and scaling).
  • Strong communication and technical writing skills.
  • Ability to empathize with users and champion for their experience.

Nice to have

  • Experience building semantic layers that serve both human analysts and programmatic/AI consumers.
  • Experience with data governance frameworks, metric versioning, or data product catalogs.
  • Familiarity with LLM-friendly data interfaces; designing schemas and metadata that enable AI agents to discover and query data effectively.
  • Experience with data validation and quality frameworks (e.g., Monte Carlo, Great Expectations).

What the JD emphasized

  • AI agents to reason over and query the semantic layer
  • AI coding tools
  • active daily use

Other signals

  • semantic model architecture
  • Agentic Analytics
  • AI agents to reason over and query the semantic layer
  • AI coding tools