Data Engineer, BI & Reporting

Veem•Toronto, ON

1d•Remote

About The Position

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, and 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, and automate reporting workflows, while also supporting 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.

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 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, 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