Posted today · be early
Engineering Manager, Data Foundations
ServiceTitan
IndiaremotePosted today
Skill Required
Data-EngineeringEngineering-ManagementData-Platform-EngineeringTechnology-LeadershipSoftware-Engineering-ManagementData-Engineering-ManagerData-Foundations-EngineeringEngineering-ManagerData EngineerEngineering ManagerEngineeringsoftware engineeringSystem DesignSOCKubernetesObservabilitySnowflakesimilar)buildingAirflowetc.)PythondesignKafkaClouddbtETLandAIFulltime
Key highlights
- 8+ years in data or software engineering, with 2+ years managing teams of 5 or more
- Lead a global team across the US and India
- Hands-on technical leadership role with architecture guidance
- Experience with Kafka, Snowflake, Airflow, and distributed systems
- Manage data ingestion, quality, and cost optimization at scale
- Focus on async-first collaboration and cross-time-zone team leadership
Role overview
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. The role requires staying 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.
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.
Requirements
- Experience: 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 have
- Experience 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.
Additional details
- Being 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.
- Originally posted on Himalayas
