Senior Manager, AI-Driven Analytics Engineering

Gohyred; United States; Hybrid; USD 152,000 - 312,000; Full time

Job summary

Toast is seeking a Senior Manager, Analytics Engineering to lead the core Analytics layer in our enterprise data warehouse and set data modeling strategy that enables federated analytics across domains. You will guide a team of analytics engineers, align with product and engineering leadership, and drive scalable, AI-ready data solutions across the organization.

You will work in a hybrid model with top-tier stakeholders and a focus on governance, performance, and long-term architecture while

Qualifications

• 8+ years in BI, Analytics, or Data Engineering roles.
• 2+ years leading a team of analytics or data engineers.
• 5+ years developing data modeling strategies at scale.
• 4+ years developing in dbt.
• Ability to translate business needs into data models.
• Strong proficiency in SQL for performance-focused queries.
• Proven ability to influence senior stakeholders and drive alignment.
• Thrives in fast-paced environments with ambiguity.

Responsibilities

• Own strategy and roadmap for hub & spoke data architecture across domains.
• Lead core Analytics layer in the data warehouse to meet domain needs.
• Define vision for an AI-ready semantic layer across business domains.
• Build, manage, and develop analytics engineers; set growth paths.
• Partner with senior stakeholders, product, and engineering to align data priorities.
• Represent analytics strategy in cross-functional and leadership forums.
• Collaborate with data engineering leadership to ensure scalable architecture.
• Provide mentorship and career development for team members.

Skills

BI & Analytics

Data Engineering

SQL

Team Leadership

dbt

Stakeholder Management

Tools

dbt

Job description

Toast is seeking a Senior Manager, Analytics Engineering to lead the core Analytics layer in our enterprise data warehouse and set data modeling strategy that enables federated analytics across domains. You will guide a team of analytics engineers, align with product and engineering leadership, and drive scalable, AI-ready data solutions across the organization.

You will work in a hybrid model with top-tier stakeholders and a focus on governance, performance, and long-term architecture while