Data Engineer, BI & Reporting

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

Originally posted on Himalayas