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About the Role
Lead two data and analytics teams, Emburse Analytics and Travel Analytics, transforming travel and expense data into customer-facing dashboards, embedded reports, and AI-powered insights. Focus on people management, SDLC ownership, product partnership, and technical decision-making in a hybrid role.
Responsibilities
- Lead, develop, coach, and assess two individual contributor teams across North America and Europe.
- Grow a collaborative team culture grounded in trust, open feedback, and accountability.
- Champion agile ways of working and continuously improve team rituals.
- Break large initiatives into small, incremental slices that deliver value early and often.
- Own the team's SDLC end-to-end, from refinement and estimation through testing, release, and post-release monitoring.
- Partner closely with Product, presenting clear options with tradeoffs in scope, timeline, cost, and risk.
- Drive predictable delivery through realistic commitments and visible progress tracking.
- Build secure, compliant practices (SSDLC, GDPR, data residency, access controls) into the regular workflow.
- Deliver accurate, reliable data pipelines, models, and dashboards on budget and on time.
- Establish data quality standards so customers trust the numbers.
- Improve engineering quality and efficiency through automation, test coverage, and cost management.
- Hire qualified candidates to strengthen company and team.
- Represent the analytics engineering teams across the organization.
- Serve as the primary engineering partner to Analytics and Travel product owners.
- Collaborate with cross-functional peers, vendor partners, and leaders to deliver projects.
Requirements
- 8+ years of data engineering, analytics engineering, or software development experience.
- 3+ years of direct line management experience, including leading multiple teams.
- Sufficient technical depth in data pipelines, data modeling, and BI to evaluate designs and assess risk and effort.
- Accountable for the quality and security of customer-facing embedded analytics (Looker and Power BI) and the analytics roadmap.
- Experience leading delivery of embedded analytics or AI analytics in a multi-tenant SaaS product.
- Prior experience in the corporate travel, booking, or expense domain.
- Understanding of secure data practices and least-privilege access.
- Strong understanding of dimensional modeling and common data design patterns.
- Ability to write clear, concise documentation.
- Candidates need to be legally allowed to work in Canada.
Skills
- Looker
- Power BI
- Snowflake
- MS Fabric
- dbt
- Airflow
- AWS
- Azure
- Data pipelines
- Data modeling
- BI
- Agile
- SDLC
- Secure data practices
- Dimensional modeling
- AI analytics
Location
- Toronto
Work Type
- Hybrid
- Onsite
Experience Level
- Senior
Education Level
- Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent years' experience
Benefits
- Competitive pay
- Flexible work
- Inclusive, collaborative environment
About the Company
- Emburse is a leader in expense intelligence, creating a future where technology drives business value and inspires extraordinary results.
- Our AI-powered platform helps organizations modernize financial operations, increase visibility, and optimize spend across the enterprise.
- We serve 12M+ users across 120 countries, helping businesses modernize their finance operations.
- Work alongside some of the brightest minds in finance, tech, and AI to solve real-world challenges.
- Your work here drives efficiency, innovation, and smarter financial decision-making for businesses everywhere.
Equal Opportunity
- Emburse provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics.
- In addition to federal law requirements, Emburse complies with applicable state and local laws governing nondiscrimination in employment in every location where the company has facilities.
- This policy applies to all terms and conditions of employment.