Engineering Manager, Data Platform

## About the Role The Engineering Manager, Data Platform role at ServiceTitan is a critical position that requires a unique blend of technical expertise and leadership abilities. As the leader of the data and reporting platform team, you will be responsible for the technical direction and day-to-day execution of a team building the data infrastructure that powers the enterprise. This role matters because it directly impacts the reliability, scalability, and performance of the platform, which in turn affects the entire organization's ability to make data-driven decisions.

The team you will be leading consists of 5+ data engineers, and your primary responsibility will be to set clear expectations, provide regular feedback, and invest in their career development. You will also be responsible for driving architectural decisions across the platform, with a particular focus on data sharing and semantic layer design. Your experience in designing complex data systems and your proficiency in modern tooling like dbt will be essential in guiding the team through technical challenges.

In terms of reporting structure, you will be working closely with product managers and architects to define and deliver the data platform roadmap. Your ability to translate business requirements into technical priorities and communicate trade-offs clearly will be crucial in ensuring that the platform aligns with business needs.

## What You Will Do - Lead and mentor a team of 5+ data engineers, providing guidance on technical and career development aspects - Drive architectural decisions across the platform, focusing on data sharing and semantic layer design - Ensure systems are built for high availability, scalability, and security - Guide the team through complex technical challenges, including semantic modeling, data mesh patterns, and platform reliability - Hold a high bar for code quality, testing, and observability - Lead efforts to improve query performance and platform efficiency - Collaborate with product managers and architects to define and deliver the data platform roadmap - Translate business requirements into technical priorities and communicate trade-offs clearly - Own the operational posture of the platform, including monitoring, alerting, incident response, and on-call rotation management - Establish and report on team-level operational metrics - Define engineering best practices and champion shift-left data governance, including data quality, lineage, and access control

## What We Are Looking For - 8+ years of experience in data or software engineering, with 2+ years managing engineering teams of 5 or more - Proven experience designing complex data systems, with specific expertise in semantic layering and data sharing at enterprise scale - Deep, hands-on experience with dbt and semantic models (e.g., MetricFlow), including designing and scaling semantic models in production - Strong proficiency with Snowflake and SQL - Experience with Spark, Python, and Snowpark is a plus - Hands-on experience with technologies such as Cursor, Claude CLI/Code, Kibana, and Airflow - Experience owning on-call processes, managing incidents, and defining operational metrics that drive team accountability - Solid command of CI/CD practices (e.g., GitHub Actions) and data observability tooling such as DataDog or Monte Carlo - Strong written and verbal communication skills, able to align cross-functional stakeholders and articulate technical trade-offs

## Nice to Have - Experience with cloud-based data platforms and migration strategies - Knowledge of data governance and security best practices - Familiarity with agile development methodologies and version control systems

## Benefits and Perks - Flexible work arrangements, including remote work options - Recognition and support for autonomous work, including professional development opportunities - Competitive compensation and benefits package - Opportunity to work with a cutting-edge technology stack and contribute to the development of a scalable data platform - Collaborative and dynamic work environment with a team of experienced professionals - Access to the latest tools and technologies, including dbt, Snowflake, and Spark - Opportunities for career growth and advancement within the company

- Tip: Make sure you have a strong understanding of data sharing and semantic layer design principles, as well as experience with modern tooling like dbt.

• To stand out, highlight your ability to balance technical leadership with people management, and showcase your experience in driving architectural decisions and guiding teams through complex technical challenges.
• When preparing for the interview, focus on your proficiency in Snowflake, SQL, and data observability tooling, and be ready to provide examples of your experience in managing on-call processes and defining operational metrics.
• It's essential to demonstrate your ability to communicate technical trade-offs clearly and align cross-functional stakeholders, so practice articulating technical concepts in simple terms.
• Consider including examples of your experience with data governance and security best practices in your application, as well as any relevant certifications or training in data engineering and management.
• Be prepared to discuss your approach to leading and mentoring a team of data engineers, and how you would handle conflicts or performance issues within the team.