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 managed engineering teams. Ideal candidates will meet most, if not all, of the following criteria.

As our Senior Manager, Data Engineering, 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 and stay abreast of new technologies and industry trends. Incorporate new ideas that are well suited to advance the goals of ServiceTitan.
• Hire, manage, grow and retain a high performance team that can meet both present and future needs by increasing and scaling data-driven decision making across the organization.
• Partner with Data Science, IT, and other organizations to ensure effective reporting, dashboards, insights, analytics, and data-driven decision making are 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 REST.
• Demonstrated ability to adapt to new technologies and learn quickly
• Strong written and presentation communication skills

Preferred Technologies

• Data warehousing and data modeling
• Azure (Data Factory, Data Lake, SQL Data Warehouse
• Microsoft Business Intelligence (Power BI)
• Microsoft SQL Server, PostgreSQL
• Data reporting and visualization

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