Data Engineer BI and Reporting
Veem is a payments company offering domestic and international payables and receivables services. Its platform supports bank transfers, cards, multi-currency wallets, payment automation, invoicing, and accounting integrations for businesses.
Funding history
About Veem
Veem provides a business payments platform for sending, receiving, managing, and automating domestic and international payments across more than 100 countries and 80 currencies. Its offerings include bank transfers, debit and credit card payments, virtual cards, virtual bank accounts, a multi-currency wallet, payment tracking, approvals, mass payments, invoices, payment links, and accounting integrations. It also provides partner solutions for financial institutions, payment service providers, AP/AR platforms, freelance marketplaces, and accountants.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own and scale reporting and analytics infrastructure, build SQL and dbt models, maintain dashboards and recurring reports, automate reporting workflows, improve data quality and governance, and support AI-driven reporting and quality-assurance systems.
Requirements
- 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, and transformation pipelines
- Experience with BI tools such as Looker, Tableau, Power BI, Metabase, Sigma, Hex, or Mode
- Experience maintaining production dashboards and recurring reports
- Experience with data quality assurance, monitoring, and reporting automation
- Strong documentation habits and a quality-assurance mindset
- Ability to independently own reporting infrastructure and workflows
Responsibilities
- Build and maintain scalable SQL and dbt data models, marts, semantic layers, and reporting datasets
- Clean, structure, and document complex data systems
- Develop trusted reporting foundations for business teams
- Improve data consistency, metric governance, and reporting standards
- Own production dashboards, recurring reports, KPI packs, and reporting workflows
- Define KPIs, business logic, and reporting requirements with stakeholders
- Ensure dashboard accuracy, reliability, and usability
- Build or manage automated reporting workflows and monitoring systems
- Support AI agents for reporting quality assurance, data quality, KPI generation, dashboard monitoring, reporting automation, metric documentation, and data freshness checks
- Implement data quality assurance, validation, monitoring, and alerting
- Troubleshoot reporting discrepancies and data issues proactively
Benefits
- Health benefits
- Fully remote work
