Archived listing. The details below describe a past opening.
Role: Data Engineer
Location: Fully Remote (Canada, EST time zone)
Compensation: Salary + Bonus + Health Benefits
About Veem
Veem is transforming global money movement. Traditional cross-border payments are slow, expensive, and opaque - we’ve built a platform that makes them seamless, transparent, and scalable.
Our solution combines global payments, FX optimization, and embedded financial tools to help businesses - from SMBs to large platforms - operate and grow internationally with confidence.
We take a partner-first approach, working closely with customers to unlock revenue opportunities and drive real business impact.
Why Join Veem
- Impact: Help businesses move billions globally, more efficiently
- Growth: Be part of a fast-scaling fintech and embedded finance space
- Ownership: Contribute meaningfully and see results quickly
- Collaboration: Work cross-functionally across Product, Sales, and Ops
- Innovation: Shape the future of B2B payments
Job Description - Data Engineer, BI & Reporting
(Analytics Engineer / BI Engineer Hybrid)
About the Role
We’re hiring a Data Engineer, BI & Reporting to own and scale the reporting and analytics infrastructure that powers operational, revenue, customer, and executive decision-making.
This is a highly hands-on individual contributor role focused on:
- analytics engineering
- BI/reporting systems
- data modeling
- workflow automation
- AI-supported reporting operations
This is not a pure Data Analyst role and not a backend platform Data Engineer role.
The ideal candidate is an Analytics Engineer / BI Engineer hybrid who can:
- build clean SQL/dbt models
- structure scalable reporting datasets
- maintain dashboards and recurring reporting systems
- improve data quality and governance
- automate reporting workflows
- support AI-driven reporting and QA agents
You’ll partner closely with cross-functional stakeholders while owning the reliability, scalability, and governance of the reporting layer.
What You’ll Do
Analytics Engineering & Data Modeling
- Build and maintain scalable SQL/dbt data models, marts, semantic layers, and reporting datasets
- Clean, structure, and document complex or messy data systems
- Develop trusted reporting foundations for business teams
- Improve data consistency, metric governance, and reporting standards
- Design maintainable transformations and reusable analytics layers
BI & Reporting Ownership
- Own production dashboards, recurring reports, KPI packs, and reporting workflows
- Maintain and improve BI systems across business functions
- Partner with stakeholders to define KPIs, business logic, and reporting requirements
- Ensure dashboard accuracy, reliability, and usability
- Support self-serve analytics capabilities
Automation & AI-Supported Workflows
- Build or manage automated reporting workflows and monitoring systems
- Support AI agents and workflow automation related to:
- reporting QA
- data quality
- KPI generation
- dashboard monitoring
- reporting automation
- metric documentation
- data freshness checks
- Review automated outputs and implement QA/governance processes
- Help transform manual reporting processes into scalable automated systems
Data Quality & Governance
- Implement data QA, validation, monitoring, and alerting
- Maintain data documentation, metric definitions, and reporting standards
- Improve observability and trust in reporting systems
- Troubleshoot reporting discrepancies and data issues proactively
Requirements
Must-Have Qualifications
- 3–6 years of experience in:
- analytics engineering
- BI engineering
- reporting engineering
- data analytics
- data modeling
- reporting automation
- or similar fields
- Advanced SQL skills
- Strong hands-on dbt experience
- Experience building:
- SQL tables
- marts
- semantic layers
- reporting datasets
- transformation pipelines
- Experience with BI tools such as:
- Looker
- Tableau
- Power BI
- Metabase
- Sigma
- Hex
- Mode
- or similar
- Experience maintaining dashboards and recurring reports in production environments
- Experience with data QA, monitoring, and reporting automation
- Strong documentation habits and QA mindset
- Ability to independently own reporting infrastructure and workflows
Bonus Qualifications
Strong bonus points for candidates with:
- Fintech, payments, or B2B SaaS experience
- Experience with:
- HubSpot data
- CRM data
- revenue operations
- customer success data
- payments or transaction data
- KPI governance and metric definition experience
- Data freshness monitoring and alerting experience
- AI tooling or workflow automation experience involving:
- OpenAI
- Anthropic
- n8n
- AI agents
- reporting bots
- dashboard QA agents
- workflow orchestration
- Experience automating manual reporting workflows
What Success Looks Like
- Reporting systems are reliable, scalable, and trusted
- Dashboards and KPI definitions remain consistent across teams
- Manual reporting work is significantly automated
- Data quality issues are proactively detected and resolved
- AI-supported reporting workflows operate with strong governance and QA
