Engineering Manager, Data Foundations
ServiceTitan
Engineering Manager, Data Foundations
Job Description
Ready to be a Titan?We're looking for an experienced Engineering Manager to lead our Data Foundations team — the team responsible for data ingestion, data quality, and cost management across ServiceTitan's data platform. You'll stay hands-on and technically engaged, guiding architecture personally rather than delegating it, while building and leading a team of strong engineers across the US and India. What You'll DoLead and Mentor: Manage and grow a team of 5+ data engineers spanning multiple regions and time zones. Set clear expectations, provide regular feedback, and build a team culture rooted in ownership and psychological safety.Hands-On Technical Leadership: Stay hands-on — review architecture and code, prototype solutions to hard problems, and personally guide the team's technical direction rather than delegating all design work.Architecture, Data Quality & Cost: Drive architecture for data ingestion (Kafka, custom ETL Agent), Snowflake, and Airflow; own the strategy for data quality tooling and monitoring; and lead cost optimization efforts, balancing efficiency with reliability and long-term platform health.Operations & Stakeholder Collaboration: Own the operational posture of the platform — monitoring, alerting, incident response, and on-call — while championing data governance best practices and partnering with product, architecture, and business stakeholders to deliver the roadmap. What You'll BringExperience: 8+ years in data or software engineering, with 2+ years managing engineering teams of 5 or more.Building & Leading Global Teams: Proven experience building and leading engineering teams across multiple regions and time zones, with strong async-first habits and comfort setting technical direction without relying on overlapping hours.Technical Depth: Hands-on experience with Cloud Providers, Kubernetes, Kafka, Snowflake, Iceberg/Delta/Hudi, Airflow, and Python; a strong grasp of distributed systems trade-offs; and experience architecting data ingestion, quality, and cost-optimization solutions at scale.Communication & Collaboration: Direct, empathetic, and outcome-focused. Able to align cross-functional stakeholders, articulate technical trade-offs, and influence architectural direction without direct authority. Nice to HaveExperience with CDC patterns and tooling (Debezium or similar).Familiarity with dbt or modern transformation frameworks.Prior experience building or standing up a new team or engineering hub in a new region.Experience with AI-assisted engineering tooling (Cursor, Copilot, Claude Code, etc.) or building AI-powered agents for operational use cases.Be Human With Us: Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway. We need amazing people like you to help us challenge the conventional and think differently about the problems that we’re solving. We’re in this together. Come be human, with us. Use of AI Technology:We use technology, including automated and AI-assisted tools, to support certain aspects of our recruitment process. These tools are designed to improve efficiency and enhance the candidate experience. AI tools are not used to make hiring decisions; all hiring decisions are made by our hiring teams.At ServiceTitan, we celebrate individuality and uniqueness. We believe that the convergence of fresh perspectives and experiences from all walks of life is what makes our product and culture so great. We do not discriminate against employees based on race, color, religion, sex, national origin, gender identity or expression, age, disability, sexual orientation, or any other characteristic protected by applicable laws.
Locations
- India Remote (Remote)
Skills Required
- and leading engineering teams across multiple regionsintermediate
- Cloud Providersintermediate
- CDC patternsintermediate
- dbtintermediate
- or standing up a new teamintermediate
- AI-assisted engineering toolingintermediate
Required Qualifications
- Experience: 8+ years in data or software engineering, with 2+ years managing engineering teams of 5 or more. (experience, 8 years)
- Building & Leading Global Teams: Proven experience building and leading engineering teams across multiple regions and time zones, with strong async-first habits and comfort setting technical direction without relying on overlapping hours. (experience)
- Technical Depth: Hands-on experience with Cloud Providers, Kubernetes, Kafka, Snowflake, Iceberg/Delta/Hudi, Airflow, and Python; a strong grasp of distributed systems trade-offs; and experience architecting data ingestion, quality, and cost-optimization solutions at scale. (experience)
- Communication & Collaboration: Direct, empathetic, and outcome-focused. Able to align cross-functional stakeholders, articulate technical trade-offs, and influence architectural direction without direct authority. (experience)
- Experience: 8+ years in data or software engineering, with 2+ years managing engineering teams of 5 or more. (experience, 8 years)
- Building & Leading Global Teams: Proven experience building and leading engineering teams across multiple regions and time zones, with strong async-first habits and comfort setting technical direction without relying on overlapping hours. (experience)
- Technical Depth: Hands-on experience with Cloud Providers, Kubernetes, Kafka, Snowflake, Iceberg/Delta/Hudi, Airflow, and Python; a strong grasp of distributed systems trade-offs; and experience architecting data ingestion, quality, and cost-optimization solutions at scale. (experience)
- Communication & Collaboration: Direct, empathetic, and outcome-focused. Able to align cross-functional stakeholders, articulate technical trade-offs, and influence architectural direction without direct authority. (experience)
Preferred Qualifications
- Experience with CDC patterns and tooling (Debezium or similar). (experience)
- Familiarity with dbt or modern transformation frameworks. (experience)
- Prior experience building or standing up a new team or engineering hub in a new region. (experience)
- Experience with AI-assisted engineering tooling (Cursor, Copilot, Claude Code, etc.) or building AI-powered agents for operational use cases. (experience)
- Experience with CDC patterns and tooling (Debezium or similar). (experience)
- Familiarity with dbt or modern transformation frameworks. (experience)
- Prior experience building or standing up a new team or engineering hub in a new region. (experience)
- Experience with AI-assisted engineering tooling (Cursor, Copilot, Claude Code, etc.) or building AI-powered agents for operational use cases. (experience)
Responsibilities
- Lead and Mentor: Manage and grow a team of 5+ data engineers spanning multiple regions and time zones. Set clear expectations, provide regular feedback, and build a team culture rooted in ownership and psychological safety.
- Hands-On Technical Leadership: Stay hands-on — review architecture and code, prototype solutions to hard problems, and personally guide the team's technical direction rather than delegating all design work.
- Architecture, Data Quality & Cost: Drive architecture for data ingestion (Kafka, custom ETL Agent), Snowflake, and Airflow; own the strategy for data quality tooling and monitoring; and lead cost optimization efforts, balancing efficiency with reliability and long-term platform health.
- Operations & Stakeholder Collaboration: Own the operational posture of the platform — monitoring, alerting, incident response, and on-call — while championing data governance best practices and partnering with product, architecture, and business stakeholders to deliver the roadmap.
- Lead and Mentor: Manage and grow a team of 5+ data engineers spanning multiple regions and time zones. Set clear expectations, provide regular feedback, and build a team culture rooted in ownership and psychological safety.
- Hands-On Technical Leadership: Stay hands-on — review architecture and code, prototype solutions to hard problems, and personally guide the team's technical direction rather than delegating all design work.
- Architecture, Data Quality & Cost: Drive architecture for data ingestion (Kafka, custom ETL Agent), Snowflake, and Airflow; own the strategy for data quality tooling and monitoring; and lead cost optimization efforts, balancing efficiency with reliability and long-term platform health.
- Operations & Stakeholder Collaboration: Own the operational posture of the platform — monitoring, alerting, incident response, and on-call — while championing data governance best practices and partnering with product, architecture, and business stakeholders to deliver the roadmap.
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