Data Engineer, BI & Reporting

Veem

1d•Remote

About The Position

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. 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

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, 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

Nice To Haves

Fintech, payments, or B2B SaaS experience
Experience with HubSpot data, CRM data, revenue operations, customer success data, or payments/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, or workflow orchestration
Experience automating manual reporting workflows

Responsibilities

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
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
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, and data freshness checks
Review automated outputs and implement QA/governance processes
Help transform manual reporting processes into scalable automated systems
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