Original listing text, shown exactly as published by the company.
What You’ll Do
- Own and evolve data architecture across ingestion, transformation, and
reporting layers, with a centralized cloud data warehouse.
- Build and maintain scalable data pipelines across a variety of internal and external data
sources, ensuring reliability, completeness, and accuracy.
- Develop robust validation frameworks to monitor data quality and quickly identify issues.
- Write and optimize complex SQL to power analytics, reporting, and business
decision-making.
- Design and maintain data models that support financial reporting, operational analytics,
and merchandising insights.
- Partner closely with Finance to ensure accurate, reconcilable reporting across revenue,
costs, and unit economics.
- Build and maintain dashboards and reporting used by leadership to drive decisions
across the company.
- Identify and resolve data issues quickly, balancing speed and accuracy in a fast-moving
environment.
- Support integrations between core business systems and ensure clean, consistent data
across platforms.
- Explore and implement AI-driven workflows that enhance data accessibility and
decision-making.
- Automate manual reporting processes and improve operational efficiency across teams.
- Act as a cross-functional partner, translating ambiguous business questions into clear,
actionable insights.
What We’re Looking For
- 5–10+ years of experience in data engineering, analytics engineering, or advanced
analytics roles.
- Strong experience with GCP and BigQuery, including materialized views, scheduled
queries, and large-scale SQL optimization.
- Experience with modern data ingestion tools—Airbyte (Cloud or OSS) strongly preferred;
comfort managing connectors, debugging sync failures, and building validation
frameworks.
- 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.
- Proven experience supporting financial reporting and working closely with finance
teams—P&L reconciliation, COGS analysis, revenue waterfalls, and unit-economics
datasets.
- Experience building dashboards and reporting in modern BI tools.
- Familiarity with AI workflows and building structured datasets for LLM-powered agents.
- Experience working across multiple business domains (ops, marketing, finance, product,
etc.).
- Strong ownership mindset with the ability to operate independently.
- Comfortable in a fast-paced, ambiguous environment with shifting priorities.
Bonus Points
- Experience with ERP or inventory management systems (especially warehouse/3PL
integrations).
- Experience in ecommerce, recommerce, logistics, or marketplace
businesses—especially Shopify-based platforms.
- Familiarity with multi-touch attribution, post-purchase surveys (e.g., Fairing/PPS), or
event-level GA4 data.
- Experience with customer cohort analysis, retention modeling, or LTV forecasting.
- Exposure to pricing, inventory aging, or supply chain/fulfillment data systems.
- Experience with Klaviyo, Attentive, or similar lifecycle marketing data integrations.
- Familiarity with demographic enrichment tools or custom API connector development.
