About the job
ServiceTitan's engineering division is on the lookout for a visionary leader to shape our data strategy, fostering sustainable growth for the future. The ideal candidate will possess expertise in big data architecture, a solid understanding of data science, and experience in managing and scaling engineering teams. Applicants should ideally meet most, if not all, of the following qualifications.
As the Senior Manager of Data Strategy, your responsibilities will include:
- Defining, prioritizing, and executing a comprehensive strategy, architecture, and implementation plan for platforms and tools that enable real-time, data-driven decision-making and customer insights across the entire ServiceTitan product suite.
- Establishing a coherent technology roadmap for data products, aligning engineering efforts with broader company objectives, focusing on both immediate wins and scalable long-term capabilities.
- Designing robust architectural frameworks for both internal and external data entities, and developing methodologies for data pipeline, storage, retention, and integration, including overall data governance.
- Researching and remaining updated on new technologies and industry trends, integrating suitable innovations to propel ServiceTitan's objectives.
- Hiring, managing, and nurturing a high-performance team capable of meeting current and future demands by enhancing data-driven decision-making across the organization.
- Collaborating with Data Science, IT, and other departments to ensure effective reporting, dashboards, insights, analytics, and data-driven decision-making are accessible to the business.
- Ensuring that tools utilized are appropriate for the tasks at hand, incorporating AI/ML technologies when necessary.
- Facilitating the integration of data collection with data science requirements, both for model development and real-time execution.
- Developing and implementing mechanisms for data quality validation and ongoing improvement.
For success in this role, you will need:
Preferred Experience:
- Knowledge of AI & Machine Learning
- Familiarity with infrastructure automation technologies like Docker and Kubernetes
- Experience with Event-Driven Architecture
- Proficient in developing architectures for processing data at scale and with low latency
- A strong grasp of integration methods, APIs, and services utilizing REST
- A demonstrated ability to adapt to new technologies and learn swiftly
- Exceptional written and verbal communication skills
Preferred Technologies:
- Data warehousing and data modeling
- Azure (including Data Factory, Data Lake, SQL Data Warehouse)
- Microsoft Business Intelligence (Power BI)
- Microsoft SQL Server, PostgreSQL, and other relevant technologies
