Principal Software Engineer, Data Platform

ServiceTitan is a company focused on delivering high-quality data and BI products. They are seeking a Principal Engineer to own the semantic model architecture of their data platform, ensuring it serves as the single source of truth for business metrics and logic while collaborating with various teams to meet product requirements.

Responsibilities:

• 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
• Define the standards for how semantic models are authored, versioned, tested, and governed
• Evaluate and drive the semantic layer technology strategy (e.g., dbt MetricFlow or equivalent)
• Architect how the semantic layer is consumed across three distinct product surfaces: Data Sharing, Reporting, and Agentic Analytics
• Partner with adjacent teams to ensure the semantic layer meets each product’s unique requirements
• Own query performance, materialization strategies, pre-aggregation patterns, and cost optimization
• Ensure the semantic layer is highly performant and scalable as data volumes and consumer demand grow
• Build the semantic layer as a true platform experience: self-service metric onboarding, developer-friendly abstractions, clear documentation, data validation, and governance guardrails
• Make it easy for other teams to extend the semantic layer without compromising consistency or quality
• Operate as a technical leader across the Data & Reporting Platform organization
• Participate in and drive design sessions across teams
• Mentor engineers, manage stakeholder and leadership alignment
• Contribute to architecture decisions that span from data foundations through reporting and analytics
• Champion high-quality code with corresponding test coverage
• Use AI coding tools (Claude, Cursor, Copilot) as a core part of your daily workflow
• Drive adoption patterns, build team-specific contexts and workflows, and set the standard for how the team multiplies velocity through AI-assisted development

Requirements:

• 10+ years of experience in Software Engineering or Data Engineering roles, including experience with large-scale, high-traffic, fault-tolerant systems
• 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; not just familiarity, but active daily use
• 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
• B.S., M.S., or PhD in Computer Science or a related field
• 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)