Data / Business Intelligence Analyst

# Data / Business Intelligence Analyst

## About the Role

We are looking for a Data / Business Intelligence Analyst to develop and maintain internal data systems that help teams make better decisions through accurate reporting, clear data visualizations, and reliable business insights.

In this role, you will oversee data across marketing and operations, bringing together information from multiple platforms and ensuring that data is accurate, connected, and up to date. You will help define key business metrics, build reports and dashboards, and become a trusted resource for data-related questions across the organization.

Our data currently lives across e-commerce platforms, advertising platforms, ERP systems, and logistics systems, and these sources do not always align. A major focus of this role will be consolidating and reconciling these sources, establishing consistent metric definitions, and building reliable reporting processes.

You will also own contribution margin reporting, providing visibility into profitability by brand, channel, and SKU. This role will work cross-functionally with Marketing, Operations, Leadership, and the development team.

## Key Responsibilities

### Contribution Margin Reporting

* Own the contribution margin reporting project end to end, from scoping and development through implementation and ongoing maintenance.
* Report CM1, CM2, and CM3 by brand, channel, and SKU.
* Establish and maintain consistent definitions for key metrics, including net revenue, COGS, fees, marketing spend, and CM1–CM3.
* Ensure the organization is working from one consistent set of financial and operational metrics.
* Monitor margin performance and identify anomalies or significant changes.
* Investigate and explain the drivers behind changes in contribution margin.

### Marketing Data & Dashboards

* Serve as the primary data partner for the Marketing team.
* Build and maintain dashboards, reports, and analyses based on business needs.
* Pull, consolidate, and reconcile advertising data across platforms such as Amazon Ads, Meta, TikTok, and other relevant channels.
* Track key marketing metrics including spend, ROAS, TACoS, CAC, and new-to-brand performance by brand, channel, and campaign.
* Connect marketing spend to contribution margin to evaluate the profitability and effectiveness of marketing investments.
* Maintain accurate and up-to-date marketing dashboards.
* Proactively identify reporting needs and opportunities to improve marketing visibility through data.

### SKU, ERP & Operations Data

* Partner with Operations to maintain accurate SKU data across multiple sales channels.
* Manage complex SKU relationships where multiple channel-specific SKUs and ASINs map to a single canonical SKU.
* Support the maintenance and accuracy of ERP and inventory data.
* Help Operations troubleshoot data inconsistencies, anomalies, and reporting issues.
* Identify opportunities to improve data processes and reduce recurring data quality issues.

### Data Quality & AI Enablement

* Reconcile internal reporting against source platforms to ensure accuracy and consistency.
* Develop and maintain data quality checks that identify issues before they impact business reporting.
* Maintain clean, efficient, and reliable semantic layers and curated queries used by internal AI tools and agents.
* Optimize data queries and structures for accuracy, speed, and cost efficiency.
* Serve as a trusted point of contact for business and data-related questions across the organization.

## First 90 Days

### Days 1–30

* Audit current contribution margin reporting and underlying data sources.
* Establish and document clear CM1–CM3 definitions.
* Identify and prioritize key data risks and inconsistencies.
* Document key decisions, assumptions, and recommended improvements.
* Develop an action plan to clean up and streamline existing data processes.

### Days 31–60

* Launch an initial contribution margin dashboard by brand and channel.
* Ensure reporting reconciles with source systems within an agreed-upon tolerance.
* Take ownership of delivering and maintaining the weekly marketing dashboard.
* Begin addressing key data quality and reporting gaps.

### Days 61–90

* Expand contribution margin reporting to the SKU level.
* Implement marketing spend attribution.
* Establish automated data quality checks.
* Address and reduce the Marketing team's outstanding dashboard and reporting needs.
* Continue improving the reliability and efficiency of the company's data processes.

## Qualifications & Requirements

* Proven experience owning complex data projects involving multiple data sources from start to finish.
* Experience working in an e-commerce, CPG, retail, or consumer-focused business is highly preferred.
* Strong SQL skills.
* Proficiency with Python and APIs.
* Experience with BigQuery and dbt.
* Experience with a BI and data visualization tool such as Looker, Tableau, Power BI, or similar.
* Experience working with e-commerce data from platforms such as Amazon Seller Central, Amazon Ads, TikTok Shop, and/or Shopify is a strong plus.
* Experience with inventory, ERP, supply chain, or operations data is a plus.
* Strong understanding of data reconciliation, data quality, and reporting processes.
* Ability to independently drive projects from scoping through completion.
* Strong documentation skills, including the ability to clearly communicate assumptions, decisions, and data definitions.
* Ability to identify and flag data issues proactively.
* Strong communication skills, with the ability to explain complex or messy data problems to non-technical stakeholders.
* Highly detail-oriented with a strong focus on data accuracy and consistency.
* Comfortable working cross-functionally with technical and non-technical teams.

Skills

- Strong SQL skills, comfort with Python and APIs, experience owning complex data projects with multiple data sources from start to finish, and experience in e-commerce or CPG business is a large plus.

Experience with Amazon Seller Central, Amazon Ads, TikTok Shop or Shopify data, inventory or supply chain data experience, and BigQuery, dbt and a BI tool like Looker or Tableau.