Enterprise Analytics Engineering Lead

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

Benefits offered by this job

Hybrid work

Competitive pay

Total rewards

Job summary

Toast is hiring a Senior Manager, Analytics Engineering to lead the core Analytics layer in our enterprise data warehouse and shape data modeling and governance at scale. You will build and grow a team of analytics engineers, align with product, engineering, and business stakeholders, and guide the AI-ready semantic layer across domains, balancing long-term architecture with near-term business needs.

This role offers a hybrid work model and a clear path to influence Toast's data strategy across

Qualifications

• 8+ years experience in BI, Analytics, or Data Engineering.
• 2+ years leading analytics or data engineering teams.
• 5+ years developing data modeling at scale.
• 4+ years developing in dbt.
• Ability to translate business needs into data models.
• Highly proficient SQL, focus on performance.
• Proven ability to influence senior stakeholders.
• Comfortable operating under ambiguity in a fast-paced environment.

Responsibilities

• Own strategy and roadmap for hub-and-spoke data architecture.
• Lead core Analytics layer in the data warehouse.
• Set vision for AI-ready semantic layer across domains.
• Build and develop a team of analytics engineers.
• Partner with stakeholders across the org on priorities.
• Represent EDS's analytics strategy in leadership forums.
• Collaborate with data engineering leadership for scalable platform.
• Provide technical and people leadership and career development.

Skills

BI Analytics

Team leadership

Data modeling

DBT

SQL

Stakeholder mgmt

Ambiguity tolerance

Cloud DW

Tools

Airflow

Sigma

Hex

Snowflake

Python

dbt

Job description

Toast is hiring a Senior Manager, Analytics Engineering to lead the core Analytics layer in our enterprise data warehouse and shape data modeling and governance at scale. You will build and grow a team of analytics engineers, align with product, engineering, and business stakeholders, and guide the AI-ready semantic layer across domains, balancing long-term architecture with near-term business needs.

This role offers a hybrid work model and a clear path to influence Toast's data strategy across