REBEL is the first and largest tech platform transforming retail’s $1 trillion returns problem into a smarter, more sustainable model. As the only Certified B Corporation returns recommerce marketplace backed by top-tier investors, we’re leading the returns revolution—partnering with over 2,500 top brands to give shoppers unbeatable deals of up to 70% off on open-box products, while keeping millions of pounds of returns out of landfills every year.

Candidates must be authorized to work in the United States. At this time we are only able to consider candidates who are based in Connecticut, Georgia, Nevada, New York, North Carolina, Tennessee, or Washington.

The Role

We’re looking for a hands-on Senior Data Engineer / Analytics Engineer to own and evolve REBEL’s data platform, reporting layer, and AI-driven data capabilities.

You’ll report directly to the Head of Data & Analytics and operate as a high-impact individual contributor across finance, operations, merchandising, marketing, and product. This is a builder role, not a people manager role.

You’ll be expected to move quickly, work scrappily, and take ownership from problem definition through implementation. This role is ideal for someone who thrives in a startup or scale-up environment, where speed, iteration, and pragmatism matter more than perfection.

What You’ll Do

1. Own and evolve REBEL’s data architecture across ingestion, transformation, and reporting layers, with a centralized cloud data warehouse.
2. Build and maintain scalable data pipelines across a variety of internal and external data sources, ensuring reliability, completeness, and accuracy.
3. Develop robust validation frameworks to monitor data quality and quickly identify issues.
4. Write and optimize complex SQL to power analytics, reporting, and business decision-making.
5. Design and maintain data models that support financial reporting, operational analytics, and merchandising insights.
6. Partner closely with Finance to ensure accurate, reconcilable reporting across revenue, costs, and unit economics.
7. Build and maintain dashboards and reporting used by leadership to drive decisions across the company.
8. Identify and resolve data issues quickly, balancing speed and accuracy in a fast-moving environment.
9. Support integrations between core business systems and ensure clean, consistent data across platforms.
10. Explore and implement AI-driven workflows that enhance data accessibility and decision-making.
11. Automate manual reporting processes and improve operational efficiency across teams.
12. Act as a cross-functional partner, translating ambiguous business questions into clear, actionable insights.

What We’re Looking For

1. 5–10+ years of experience in data engineering, analytics engineering, or advanced analytics roles.
2. Strong experience with GCP and BigQuery, including materialized views, scheduled queries, and large-scale SQL optimization.
3. Experience with modern data ingestion tools—Airbyte (Cloud or OSS) strongly preferred; comfort managing connectors, debugging sync failures, and building validation frameworks.
4. Strong proficiency in SQL and data modeling, with comfort using AI tools (e.g., Claude Code) to accelerate development. You should be fluent in CTEs, window functions, UNION ALL patterns, date-spine techniques, and anti-join logic.
5. Proven experience supporting financial reporting and working closely with finance teams—P&L reconciliation, COGS analysis, revenue waterfalls, and unit-economics datasets.
6. Experience building dashboards and reporting in modern BI tools.
7. Familiarity with AI workflows and building structured datasets for LLM-powered agents.
8. Experience working across multiple business domains (ops, marketing, finance, product, etc.).
9. Strong ownership mindset with the ability to operate independently.
10. Comfortable in a fast-paced, ambiguous environment with shifting priorities.

Bonus Points

1. Experience with ERP or inventory management systems (especially warehouse/3PL integrations).
2. Experience in ecommerce, recommerce, logistics, or marketplace businesses—especially Shopify-based platforms.
3. Familiarity with multi-touch attribution, post-purchase surveys (e.g., Fairing/PPS), or event-level GA4 data.
4. Experience with customer cohort analysis, retention modeling, or LTV forecasting.
5. Exposure to pricing, inventory aging, or supply chain/fulfillment data systems.
6. Experience with Klaviyo, Attentive, or similar lifecycle marketing data integrations.
7. Familiarity with demographic enrichment tools or custom API connector development.

Why You’ll Love Working at REBEL

1. High ownership IC role: Build and own critical systems without layers of management.
2. AI-forward: Work on real, practical AI applications across data and operations—not hypothetical use cases.
3. Direct business impact: Your work will influence finance, ops, merchandising, and product decisions daily.
4. Startup energy: Move fast, ship quickly, and see immediate results.
5. Purpose with impact: Help solve the $1T returns problem while enabling consumers to Shop Smarter™.

Pay Transparency

This is a full-time, exempt position eligible to receive a base salary. Final salary offered will be determined based on factors including but not limited to the candidate’s skills and experience.

Initial base salary range for this remote position = $100,000 – $170,000

Equal Opportunity

REBEL is committed to employing a diverse workforce and is proud to be an Equal Opportunity Employer. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, disability, pregnancy, or any other characteristics protected by law. REBEL is committed to compliance with all applicable fair employment practice laws. If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please contact careers@fromrebel.com

REBEL may, from time to time, use AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

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