Data / Analytics Engineer (eCommerce)

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