Senior Manager of Analytics Engineering

Toast; United States; Sur place; USD 180 000 - 240 000; Plein temps

Avantages offerts par ce poste

Unlimited Vacation

401(k) and matching

Medical, Dental, & Vision Coverage

Sabbatical after five years

Professional Development Reimbursement

Résumé du poste

Toast is seeking an experienced Analytics Engineering Lead to own the strategy and roadmap for a hub-and-spoke data architecture. You will lead the core Analytics layer in our data warehouse and guide an AI-ready semantic layer across business domains.

You will build and mentor a team of analytics engineers, partner with senior business and engineering stakeholders, and drive alignment on data analytics priorities across the organization.

Qualifications

• 5+ years experience developing data modeling strategies at scale
• Thrives in a fast-paced environment and comfortable operating under ambiguity
• 8+ years experience in Business Intelligence, Analytics, and/or Data Engineering roles
• Demonstrated ability to influence senior stakeholders and drive alignment
• 2+ years experience managing or formally leading a team of analytics or data engineers
• 4+ years experience developing in dbt

Responsabilités

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

Connaissances

Data architecture

Leadership

SQL proficiency

Stakeholder management

Mentoring

Data modeling

Team building

Outils

dbt

Airflow

Snowflake

Sigma

Hex

Python

Description du poste

• Own the strategy and roadmap for a hub & spoke data architecture, and drive alignment on it across domain teams


• Lead the team that builds and maintains the core Analytics layer in our data warehouse, ensuring it meets the needs of the domain teams building on top of it


• Set the vision for an AI-ready semantic layer that is extendable across business domains, and guide its execution


• Build, manage, and develop a team of analytics engineers — hiring, coaching, and setting growth paths


• Partner with senior business stakeholders, product leadership, and engineering leadership to align on data analytics priorities across the organization


• Represent EDS’s analytics strategy in cross-functional and leadership forums


• Partner closely with data engineering leadership to ensure platform scalability and coherent architecture across teams


• Provide technical and people leadership, mentorship, and career development to team members

Benefits

• Peer and company recognition programs


• Unlimited Vacation


• Sabbatical opportunity after five years


• Professional Development Reimbursement Program


• Commitment to Employee Wellness through resources such as a quarterly Wellness Stipend


• Various peer and company recognition programs


• 401(k) and matching


• Medical, Dental, & Vision Coverage


• Subsidized backup childcare


• Mental Health Benefits

5+ years experience developing data modeling strategies at scaleThrives in a fast-paced environment and comfortable operating under ambiguity8+ years experience in Business Intelligence, Analytics, and/or Data Engineering rolesDemonstrated ability to influence senior stakeholders and drive alignmentHighly proficient in SQL, with a focus on query design and performanceAbility to understand the business needs behind data modeling decisions2+ years experience managing or formally leading a team of analytics or data engineers4+ years experience developing in dbtExperience with Sigma, Hex, and/or other BI dashboard toolsExperience with AirflowExperience in cloud-based data warehouses, specifically SnowflakeExperience with PythonExperience building or scaling a data/analytics engineering functionExperience in a SaaS or FinTech focused enterprise