Data / Analytics Engineer (eCommerce) to $3000

We are looking for a highly skilled Data / Analytics Engineer to take ownership of our analytics layer across a modern DTC and subscription-based business.

This role sits at the intersection of data engineering, analytics, and business decision-making. You will be responsible for ensuring data accuracy, defining key metrics, and translating complex datasets into actionable insights used across product, marketing, and leadership.

Key Responsibilities

• Design, build, and maintain scalable data models across multiple sources (Shopify, Stripe, App Store, Amazon, etc.)
• Develop and optimize SQL queries (CTEs, window functions, multi-source joins, deduplication)
• Build and maintain dashboards (Grafana or similar) for real-time and operational monitoring
• Define and standardize key business metrics (LTV, cohorts, churn, ARPU, refill rates)
• Ensure data consistency across systems, including handling returns, fulfillment lag, and edge cases
• Work with ELT pipelines (e.g. Fivetran) and understand data ingestion and transformation flows
• Collaborate with product, marketing, and leadership teams to translate data into decisions
• Support investor/board-level reporting and be able to clearly explain and defend metric definitions

Requirements

• Strong SQL skills (advanced queries, performance optimization)
• Experience with data warehouses (Redshift, Snowflake, BigQuery, or similar)
• Experience building dashboards (Grafana, Tableau, Looker, or similar)
• Familiarity with Shopify, subscription models (Recharge), and eCommerce data structures
• Solid understanding of DTC metrics (LTV, retention, churn, cohort analysis)
• Experience working with ELT tools (Fivetran or similar)
• Strong analytical thinking and ability to work with imperfect data
• Ability to communicate insights clearly to both technical and non-technical stakeholders

Nice to Have

• Experience with subscription businesses or recurring revenue models
• Background in product analytics or growth analytics
• Experience with event tracking tools (Segment or similar)
• Experience with Python or data transformation frameworks (dbt, etc.)

What We’re Looking For

We are not just looking for someone who can build dashboards — we are looking for someone who can own the metric layer.

You should be comfortable answering questions like:

• How should LTV be defined for this business?
• What is the correct way to count a “customer”?
• How do returns and fulfillment delays affect revenue reporting?

This role requires both technical depth and strong business judgment.

Engagement

• Flexible: full-time or part-time
• Remote-friendly