Senior Manager, Data Strategy

Company Description About ServiceTitan ServiceTitan is the world’s leading and fastest-growing software technology platform for the trades, a trillion-dollar global industry. We help small business entrepreneurs run and grow their businesses. For more information about ServiceTitan, visit www.ServiceTitan.com. Perks & Benefits 1. Work/Life Balance: flexible work schedule, flexible PTO 2. Family-Friendly Benefits: extended parental leave, pregnancy support, 20k in adoption reimbursement, Snoo Smart Sleeper, back-up childcare credits, legal benefit, discounted pet insurance 3. Enrichment: ongoing learning culture with access to Linkedin Learning and professional development workshops, diversity charter groups, orientation program, career pathing opportunities, mentorship programs 4. Health & Wellness: company-paid medical/vision/dental/life insurance/disability, employer HSA contribution, free One Medical membership, care coordination support, 401(k) with company match, stipend for home office equipment/supplies, gym discounts, monthly cell phone stipend Equal Opportunity Employer Job Description The engineering organization at ServiceTitan is looking for a leader who will build the data strategy to support our growth now and in the future. The ideal candidate will have experience with architecture of big data platforms, understanding of data science, and have grown and [... source excerpt omitted ...] a Strategy, you will: Define, prioritize, and deliver the strategy, architecture and implementation of platforms and tools for enabling real-time, data-driven decision making and customer insights across the ServiceTitan portfolio of products. Establish a well-coordinated technology roadmap for data products, leveraging engineering in support of the broader company product and growth goals. The roadmap should deliver a mix of short-term wins and long-term capabilities for scale. Design architectural frameworks for data entities, both internal and external, and develop data pipeline, storage, retention and integration methodologies including overall data governance. Research a [... source excerpt omitted ...] available to the business. Ensure tools used are appropriate and suitable for the problem. Leverage AI/ML when necessary. Ensure integration of data collection with data science requirements both for model development and real-time model execution. Develop and implement solutions for data quality validation and continuous improvement. To be successful in this role, you'll need: Preferred Experience AI & Machine Learning understanding Infrastructure automation technologies like Docker and Kubernetes. Event Driven Architecture Experience developing architectures that process data at scale and low latency Strong understanding of integration methods, APIs and services using RES