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Engineering Manager, Data Platform
ServiceTitanEngineering Manager leading a data engineering team at ServiceTitan. Responsible for technical direction and people leadership while optimizing data systems for enterprise solutions.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in managing data engineering teams and driving architectural decisions, with a strong focus on Semantic Layer design and Data Sharing. Proficient in operational management, including monitoring, incident response, and data governance best practices.
Highest-signal resume keywords
Data Engineering ManagementSemantic Layer DesignSnowflake ProficiencyDbt ExperienceCI/CD Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringSemantic ModelingData SharingSQLIncident ManagementData GovernanceData QualityData LineagePlatform ReliabilityQuery Performance Optimization
Soft Skills
Communication SkillsTeam Leadership
Tools & Technologies
SnowflakeDbtMetricFlowCursorClaude CLI/CodeKibanaAirflowDataDogMonte CarloGitHub Actions
Industry Keywords
Data Mesh PatternsData ObservabilityOperational MetricsShift-Left Data Governance
Tech Stack
Tools & technologiesAirflowSQL
About the role
Key responsibilities & impact- Manage and grow a team of 5+ data engineers.
- Drive architectural decisions across the platform, with particular depth in Data Sharing and Semantic Layer design.
- Guide the team through complex technical challenges, including Semantic Modeling, data mesh patterns, and platform reliability.
- Lead efforts to improve query performance and platform efficiency.
- Collaborate with product managers and architects to define and deliver the data platform roadmap.
- Own the operational posture of the platform — monitoring, alerting, incident response.
- Define engineering best practices and champion shift-left data governance, including data quality, lineage, and access control.
Requirements
What you’ll need- 8+ years 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 (eg MetricFlow) — including designing and scaling semantic models in production.
- Strong proficiency with Snowflake and SQL.
- 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.
Benefits
Comp & perks- 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.
- AI tools are not used to make hiring decisions; all hiring decisions are made by our hiring teams.
- 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.