Data Engineer, BI & Reporting

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.

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 data freshness checks

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

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

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